In the planar case, one possibility to create a high quality. curve that interpolates a given set of points is to use a clothoid spline,

Size: px
Start display at page:

Download "In the planar case, one possibility to create a high quality. curve that interpolates a given set of points is to use a clothoid spline,"

Transcription

1 Dscrete Farng of Curves and Surfaces Based on Lnear Curvature Dstrbuton R. Schneder and L. Kobbelt Abstract. In the planar case, one possblty to create a hgh qualty curve that nterpolates a gven set of ponts s to use a clothod splne, whch s a curvature contnuous curve wth lnear curvature segments. In the rst part of the paper we develop an ecent farng algorthm that calculates the dscrete analogon of a closed clothod splne. In the second part we show how ths dscrete lnear curvature concept can be extended to create a farng scheme for the constructon of a trangle mesh that nterpolates the vertces of a gven closed polyhedron of arbtrary topology. x1. Introducton In many elds of computer-aded geometrc desgn (CAGD) one s nterested n constructng curves and surfaces that satsfy aesthetc requrements. A common method to create far objects s to mnmze farness metrcs, but snce hgh qualty farness functonals are usually based on geometrc nvarants, the mnmzaton algorthms can become computatonally very expensve [1]. A popular technque to smplfy ths approach s to gve up the parameter ndependence by approxmatng the geometrc nvarants wth hgher order dervatves. For some mportant farness functonals ths results n algorthms that enable the constructon of a soluton by solvng a lnear equaton system, but such curves and surfaces are n most cases not as far as those dependng on geometrc nvarants only. An nterestng approach to smplfy the constructon process wthout gvng up the geometrc ntrnscs s to use varatonal calculus to derve derental equatons characterzng the soluton of a mnmzaton problem. Mehlum [8] used ths dea to approxmate a mnmal energy curve (MEC), whch mnmzes the functonal R (s) 2 ds, wth pecewse arc segments. In [1] Brunnet and Kefer exploted the property that a segment of a MEC between two nterpolaton ponts satses the derental equaton = to speed up the constructon process usng looup tables. Curve and Surface Desgn: Sant-Malo Perre-Jean Laurent, Paul Sablonnere, and Larry L. Schumaer (eds.), pp. 371{38. Copyrght oc 2 by Vanderblt Unversty Press, Nashvlle, TN. ISBN All rghts of reproducton n any form reserved.

2 372 R. Schneder and L. Kobbelt The usage of such derental equatons based on geometrc nvarants can be seen as a reasonable approach to the farng problem n ts own rght, and t can be appled to curves as well as surfaces. For planar curves, one of the smplest derental equatons s =. Assumng arc length parameterzaton, ths equaton s only satsed by lnes, crcles and clothods. A curvature contnuous curve that conssts of parts of such elements s called a clothod splne. Most algorthms for the constructon of such curves are based on technques that construct the correspondng lne, crcle and clothod segments of the splne [9]. Ths s possble for planar curves, but the dea does not extend to surfaces. In ths paper we wll rst present a fast algorthm to construct an nterpolatng closed dscrete clothod splne (DCS) purely based on ts characterstc derental equaton. Our algorthm uses dscrete data, because ths has been proven to be especally well suted for the ecent constructon of nonlnear splnes [7]. The ecency of our constructon process s largely based on an algorthm called the ndrect approach. Ths algorthm decouples the curvature nformaton from the actual geometry by explotng the fact that the curvature dstrbuton tself s a dscrete lnear splne. Besdes the speed of the planar algorthm, t has another very mportant property: t drectly extends to the constructon of surfaces! In Secton 2 we gve a short revew of related wor. Secton 3 wll rst gve an exact denton of a DCS and then address ts ecent computaton. Secton 4 shows how the planar algorthm extends to surfaces. We construct far surfaces nterpolatng the vertces of a gven closed polyhedron of arbtrary topology by assumng a pecewse lnear mean curvature dstrbuton wth respect to a natural parameterzaton. x2. Related Wor A very nterestng algorthm addressng the problem of constructng far curves and surfaces wth nterpolated constrants was presented by Moreton and Sequn. In [1] they mnmzed farng functonals, whose farness measure punshes the varaton of the curvature. The qualty of ther mnmal varatonal splnes s extraordnary good, but due to ther extremely demandng constructon process, the computaton tme needed s enormous. Ther curves and surfaces conssted of polynomal patches. In contrast to ths approach, most farng and nonlnear splnes algorthms are based on dscrete data. Malcolm [7] extended the dscrete lnear splne concept to ecently calculate a dscrete MEC for functonal data. In [13] Welch and Wtn presented a nonlnear farng algorthm for meshes of arbtrary connectvty, based on the stran energy of a thn elastc plate. Recently, Desbrun et al. [3] used the mean curvature ow to derve a dscrete farng algorthm for smoothng of arbtrary connected meshes. In most farng algorthms the orgnal farng functonals are approxmated by smpler parameter dependent functonals. In recent years ths dea was combned wth the concept of subdvson surfaces to create varatonal

3 Dscrete Farng of Curves and Surfaces 373 subdvson splnes [12,6,4]. Especally [4] should be emphaszed here, snce our local parameterzaton needed n Secton 4 s largely based on deas presented there. Instead of mnmzng a functonal, Taubn [11] proposed a sgnal processng approach to create a fast dscrete farng algorthm for arbtrary connectvty meshes. Closely related but based on a derent approach s the dea presented by Kobbelt et al. [5], where a unform dscretzaton of the Laplace operator s used for nteractve mesh modelng. In [3] Desbrun et al. showed that a more sophstcated dscretzaton of the Laplace operator can lead to mproved results. The drect teraton approach presented later can be seen as a nonlnear generalzaton of such schemes. x3. Dscrete Clothod Splnes In ths secton we show how to nterpolate a closed planar polygon usng a dscretzaton of a clothod splne. Although the algorthms extends to open polygons wth G 1 boundary condtons n a straghtforward manner, we only consder closed curves, because that case drectly extends to surfaces. 3.1 Notaton and dentons In the followng we denote the vertces of the polygon that has to be nterpolated wth P = fp 1 ; : : : ; P n g. Let = f 1 ; : : : ; m g be the vertces of a rened polygon wth P. The dscrete curvature at a pont s de- ned to be the recprocal value of the crcle radus nterpolatng the ponts 1 ; ; +1 or f the ponts le on a straght lne, whch leads to the well nown formula det( 1 ; +1 ) = 2 jj 1 jj jj +1 jj jj +1 1 jj : (1) Denton 1. A polygon wth P s called a dscrete clothod splne (DCS), f the followng condtons are satsed: 1) The nteror of each segment s arc length parameterzed jj 1 jj = jj +1 jj, whenever 62 P, 2) The dscrete curvature s pecewse lnear: 2 = =, whenever 62 P. We wll construct a DCS usng an teraton procedure! +1 untl the above condtons are sucently satsed. The teraton starts wth an ntal polygon that nterpolates the P (Fg. 1). 3.2 Drect approach In ths approach the locaton of a vertex +1 only depends on the local neghborhood 2 ; : : : ; of ts predecessor +2. To satsfy condton 1 n Denton 1 locally, +1 has to le on the perpendcular bsector between

4 374 R. Schneder and L. Kobbelt = P m P m-1 2 P n Fg. 1. The left sde shows the update steps for n the drect and the ndrect teraton. The rght sde shows the ntal polygon. We smply subsampled the polygon P. and 1 +1 (Fg. 1), reducng the 2 varate problem to a unvarate one. Further we requre +1 to satsfy 2 +1 =. Unfortunately ths equaton s nonlnear n the coordnates of the vertces +1, but snce the update! +1 n the -th teraton step wll be small, we can lnearze the equaton by usng the coordnates of nstead of +1 n the denomnator of equaton (1). Ths allows us to update every solvng a 2 2 lnear system for +1 durng one teraton step. 3.3 Indrect approach If we decouple the curvature values +1 from the actual polygonal geometry and perform the drect teraton scheme only on the curvature values by solvng 2 +1 =, the curvature plot would converge to a pecewse lnear functon. The dea of the ndrect approach s to use ths property to create a new teraton scheme. Ths s done by dvdng each teraton step nto two sub-steps, n the rst sub-step we estmate a contnuous pecewse lnear curvature dstrbuton, and n the second sub-step we use those as boundary condtons to update the ponts. We get the curvature dstrbuton by estmatng the curvature of the polygon at every pont P j, and nterpolate ths curvature values lnearly across the nteror of the segments, assgnng a curvature estmaton ~ +1 to every vertex. In the second step ths curvature nformaton s used to update the ponts, where the poston of the new pont +1 s determned by ~ +1 and the neghborhood 1 ; ; +1 of ts predecessor (Fg. 1). Agan one degree of freedom s reduced by restrctng +1 to le on the perpendcular bsector between the ponts and 1, +1 and further we requre +1 to satsfy +1 = ~ +1. Usng an analogous lnearzaton technque as n the prevous case, we can agan update every solvng a 2 2 lnear system. It s very mportant to alternate both sub-steps durng each teraton. Snce the ~ +1 are only estmates of the nal DCS, an teraton process that merely terates the second sub-step mght not converge. Compared to the drect approach, the ndrect teraton scheme has some nterestng advantages. The nterpolaton ponts mply forces everywhere durng one teraton step; there s no slow propagaton as n the drect approach. The drect approach acts due to ts local formulaton as a lowpass lter, here because of ts global strategy the ndrect teraton s much better suted to reduce the low frequency error. One teraton step s cheaper than one teraton step of the drect approach. Ths fact wll become much more mportant

5 Dscrete Farng of Curves and Surfaces a) 1 b) 1 c) d) e) Fg. 2. a) A polygon P wth 8 vertces. b) The DCS nterpolatng the vertces of P. The structure of the polygon s equvalent to a 5 tmes subdvded P. The calculaton tme was < :1 seconds. c) Perodc C 2 cubc splne nterpolaton of P. d) Curvature plot of the DCS. e) Curvature plot of the perodc cubc splne. f we extend the algorthms to the surface case. Fnally, snce the estmated curvatures are constructed by lnear nterpolaton they are well bounded, a fact that stablzes the teraton procedure. 3.4 Detals and remars Both schemes were mplemented usng a generc multgrd scheme, a technque that has proven to be valuable when herarchcal structures are avalable [4]. We rst constructed a soluton on a coarse level, and used a prolongaton of ths coarse soluton as startng pont for an teraton on a ner level. Applyng ths strategy across several levels of the herarchy, the convergence of both approaches are ncreased dramatcally. On the coarsest herarchy level the ntal polygon was constructed by lnearly samplng the polygon P (Fg. 1). The curvature values at the nterpolaton ponts 2 P needed n the estmaton step were calculated by smply applyng formula (1) on. Wthout the multgrd approach, such a smple strategy would not be reasonable, because for ne polygons the occurrng curvature values could become too large. Our nal teraton scheme for the DCS s a combnaton of the two prmary multgrd teratons. Such an approach has the advantage that the estmated curvatures are usually better, snce the hgh frequency error near the nterpolaton ponts are smoothed out by the drect step. Ths multgrd hybrd approach turned out to be a very relable solver. All examples throughout the paper were mplemented n Java 1.2 for Wndows runnng on a PII wth 4MHz. In Fgure 2 we see that our algorthm stll produces a far soluton n cases where classcal perodc cubc splne nterpolaton usng chord length parameterzaton fals completely. In ths example we can also see why t s not only comfortable to be able to start wth such a smple ntal polygon, but also can be very mportant n some

6 376 R. Schneder and L. Kobbelt Fg. 3. Wreframe of a mesh P and the solutons of a 2 tmes resp. 3 tmes subdvded mesh. Iteraton tmes: mddle :2s, rght :4s. cases. Our algorthm searches the soluton next to the startng polygon, so tang to be a a lnearly sampled P wll prefer solutons wthout loops. A technque that would use the perodc cubc splne to ntalze n ths example would ether fal because of the enourmous curvatures that turn up, or produce a DCS wth loops. It s well nown that clothods can be parameterzed usng Fresnel Integrals [9]. If such a contnuous soluton s preferred, the dscrete soluton could be used to derve a closed form representaton. x4. Closed Surfaces of Arbtrary Topology In ths secton we want to show how to extend the concept of planar clothod splnes to closed surfaces of arbtrary topology. Gven a closed polyhedron P of arbtrary topology, we construct a dscrete far surface that nterpolates the vertces of P. To be able to extend the planar algorthms, we rst have to determne what curvature measure for surfaces has to be used. Accordng to Bonnet's unqueness problem, the mean curvature seems to be most approprate. 4.1 Notaton and dentons In the followng, we denote the vertces of the polyhedron that has to be nterpolated by P = fp 1 ; : : : ; P n g. Let = f 1 ; : : : ; m g be the vertces of a rened polyhedron wth P, where we requre the topologcal mesh structure of to be equvalent to a unformly subdvded P (Fg. 3). Because of ths structure, we can partton the vertces of nto three classes. Vertces 2 P are called nterpolaton vertces, that can be assgned to an edge of P are called edge vertces, and the remanng ponts are called nner vertces. Edge and nner vertces always have valence 6; for those ponts let ;l ; l = 1::6 be ther adjacent vertces. For edge vertces we mae the conventon that the adjacent vertces are arranged such that ;1 and ;4 are edge or nterpolaton vertces. Let H resp. H ;l be the dscrete mean curvature at resp. ;l and let n be the dscrete unt normal vector at. Fnally, let us dene the followng operators: P 1=6 6 g p ( ) = l=1 ;l; f s an nner vertex, 1=2 ( ;1 + ;4 ); f s an edge vertex,

7 Dscrete Farng of Curves and Surfaces 377 c a b c b a a c c b c a a b b d e Fg. 4. Left) Parameter doman for an nner vertex. Mddle) Parameter doman for an edge vertex. Rght) The parameter doman for an nterpolaton vertex of valence 5 s a subset of ths doman. P 1=6 6 g h (H ) = l=1 H ;l; f s an nner vertex, 1=2 (H ;1 + H ;4 ); f s an edge vertex. We are now n the poston to extend Denton 1 to the surface case. Denton 2. The polyhedron wll be called a soluton to our dscrete farng problem, f the followng condtons are satsed: 1) The vertces are regularly dstrbuted. For all edge and nner vertces, there should be a t 2 IR such that = g p ( ) + t ~n, 2) The curvature s lnearly dstrbuted over each face: g h (H ) = H. Condton 2 s straghtforward, t states that the mean curvature s changng lnearly wth respect to the barycentrc parameterzaton of the nner and edge vertces. Condton 1 s more dcult to understand. It generalzes the DCS property that vertces n the nteror of a segment were on the perpendcular bsector between ts neghbors. As n the planar case, we construct the surfaces usng an teraton! +1, startng wth an ntal polyhedron. 4.2 Dscretzaton of the geometrc nvarants Our dscretzaton technque s based on the well-nown dea of constructng a local quadratc least square approxmaton of the dscrete data and estmatng the needed geometrc nvarants from the rst and second fundamental forms. For the mean curvature H, ths means [2] H = 1 2 eg 2fF + ge EG F 2 ; (2) where E; F; G are the coecents of the rst fundamental form, and e; f; g are those of the second fundamental form of the least square approxmaton. Instead of recalculatng a local parameterzaton durng each step n the teraton, we explot the fact that our meshes are well structured to determne a local parameterzaton n advance, thus rasng the speed of our algorthms consderably. The decson, whch local parameterzaton should be assgned to a vertex was nuenced by three mayor constrants: smplcty, regularty and unqueness of the quadratc approxmaton. These constrants lead us to the followng local parameterzaton classes (Fg. 4). For nner vertces, the

8 378 R. Schneder and L. Kobbelt parameter doman s a regular hexagon, for edge vertces t s composed of two regular hexagon halves. Calculatng the matrces needed for a least square approxmaton n both cases, t s easy to see that ths parameterzatons always lead to a unque least square approxmaton. Only at the nterpolaton vertces t s not always sucent to use the 1-neghborhood. Ths s obvous f the valence v of the vertex s 3 or 4, but even f the valence s hgher, the least square approxmaton can fal n the 1-neghborhood. Usng parts of the 2- neghborhood consstng of regular sectors solves that problem. For example, the least square approxmaton s already unque by usng the 1-neghborhood and one complete sector of the 2-dsc (mared wth a,b,c n Fg. 4). Snce we are only nterested n ntrnsc values, we can use the fact that an ane mappng of the parameter doman only changes the parameterzaton of our quadratc approxmaton, but not geometrc nvarants. Ths fact allowed us to chose one xed equlateral hexagon to serve as parameter doman for all nner vertces, and guaranteed a smple update step for such ponts. At edge and nterpolaton vertces, we calculated the parameter domans by applyng the blendng technque proposed n [4]. Ths algorthm constructs a local parameterzaton that adapts to the underlyng geometry dened by P, thus approxmatng a local sometrc parameterzaton. For a detaled descrpton of that algorthm we have to refer to that wor. 4.3 Drect approach When updatng the vertex n an teraton step, the new poston s determned by the two equatons +1 = g p ( ) + t ~n and H +1 = g h (H ). Wth analogous arguments as n the curve settng, we lnearzed the mean curvature expresson (2) for H +1 by usng the vertces of to calculate the coecents of the rst fundamental form E; F; G and by replacng the normal n +1 by n when calculatng the coecents of the second fundamental form. Fnally, the vertex +1 s determned by solvng a lnear equaton for t. 4.4 Indrect approach The planar ndrect teraton scheme drectly extends to the surface settng. In the rst sub-step we estmate the mean curvature of the polyhedron at the nterpolaton vertces and use smple lnear nterpolaton to assgn a mean curvature value H ~ +1 to every edge and nner vertex. Ths means the estmated values satsfy H ~ +1 = g h ( H ~ +1 ). In the second sub-step we then use these estmated values to determne +1 usng the formula H +1 = H ~ +1 wth the same lnearzaton method as n the drect approach. 4.5 Detals and remars Snce the vertces are updated along the surface normals, the drect teraton can be nterpreted as some nd of curvature ow, where the speed s determned by a local equaton system. As was ponted out by Desbrun et al. [3], ows dependng only on local surface propertes do not have to be numercally stable for large steps durng the teraton process. To allow larger

9 Dscrete Farng of Curves and Surfaces 379 Fg. 5. Left) Tetra Thng mesh. Rght) Soluton of the multgrd ndrect teraton after the Tetra Thng has been subdvded 5 tmes. The reecton lnes ndcate that the surface s quas G 2 contnuous. Iteraton tme: 4 seconds. update steps, Desbrun et al. used the bacward Euler method to develop an algorthm called mplct ntegraton for farng of arbtrary meshes based on Laplacan and on mean curvature ow. The dea behnd ths approach s to use global surface nformaton nstead of consderng the local neghborhood only. The ndrect approach follows that dea and explots global surface propertes ecently. In the surface case the ndrect approach shows ts true power. The estmaton sub-step s mostly smple lnear nterpolaton and usng the estmated curvature, we only need the 1-neghborhood of a vertex durng ts update process. The update process for nteror vertces s especally smple because of the equlateral hexagon as parameter doman. For edge and nterpolaton vertces, we calculated the least square matrces before the rst teraton step and cached the result. Our surface examples were created usng a mutgrd teraton scheme based on the ndrect approach. As mentoned earler, the constructon of our local parameterzaton s based on the technque presented n [4], where dvded derence operators to create dscrete thn plate splnes had to be derved. A comparson of our results showed that the deas presented n ths paper allow the constructon of consderably mproved meshes wthout ncreasng the computaton tme. The mproved qualty s due to the fact that our dscrete surfaces are based on geometrc nvarants nstead of second order partal dervatves, and thus the error made by guessng an sometrc local parameterzaton n advance has less nuence. Due to the fact that we estmated the local parameterzaton once, we do not get an exact G 2 contnuty at the edges and nterpolatng ponts, but as can be seen n Fgure 5, our surfaces are good approxmatons to G 2 surfaces. To acheve true G 2 contnuty, one would have to ncrease the eort for the handlng of edge and nterpolatng vertces. Future wor wll nvestgate f such eorts are worthwhle.

10 38 R. Schneder and L. Kobbelt x5. Concluson The qualty of the resultng curves and surfaces s superor to approaches based on quadratc functonals as the thn plate energy due to the more sophstcated approxmaton of geometrc nvarants. Although our objects are nonlnear splnes, they can be calculated fast enough to be applcable n nteractve desgn. The presented deas are optmally suted for the constructon of curves and surfaces wth pecewse lnear curvature dstrbuton, but could also be extended to hgher order dscrete farng approaches. References 1. Brunnett G., and J. Kefer, Interpolaton wth mnmal-energy splnes, Computer-Aded Desgn 26(2) (1994), 137{ do Carmo, M. P., Derental Geometry of Curves and Surfaces Prentce- Hall, Inc Englewood Cls, New Jersey, Desbrun, M., M. Meyer, P. Schroder, and A. H. Barr, Implct farng of rregular meshes usng duson and curvature ow, SIGGRAPH 99 Conference Proceedngs, Kobbelt, L., Dscrete farng, Proceedngs of the Seventh IMA Conference on the Mathematcs of Surfaces '97, 11{ Kobbelt, L., S. Campagna, J. Vorsatz, and H. P. Sedel, Interactve multresoluton modelng on arbtrary meshes, SIGGRAPH 97 Conference Proceedngs, 15{ Kobbelt, L., A varatonal approach to subdvson, Comput. Aded Geom. Desgn 13 (1996), 743{ Malcolm M. A., On the computaton of nonlnear splne functons, SIAM J. Numer. Anal. 15 (1977), 254{ Mehlum, E., Nonlnear splnes, Computer Aded Geometrc Desgn, Academc Press, London, 173{27, Mee, D. S., and D. J. Walton, A guded clothod splne, Comput. Aded Geom. Desgn 8 (1991), 163{ Moreton H. P., and C. H. Sequn, Functonal optmzaton for far surface desgn, SIGGRAPH 92 Conference Proceedngs, 167{ Taubn G., A sgnal processng approach to far surface desgn, SIG- GRAPH 95 Conference Proceedngs, 351{ Wemer, H., and J. Warren, Subdvson Schemes for Thn Plate Splnes, Computer Graphcs Forum 17 (1998), 33{ Welch, W., and A. Wtn, Free-Form shape desgn usng trangulated surfaces, SIGGRAPH 94 Conference Proceedngs, 247{256. Lef Kobbelt and Robert Schneder Max-Planc-Insttut fur Informat Saarbrucen, Germany fobbelt, schnederg@mp-sb.mpg.de

Fair Triangle Mesh Generation with Discrete Elastica

Fair Triangle Mesh Generation with Discrete Elastica Far Trangle Mesh Generaton wth Dscrete Elastca Shn Yoshzawa, and Alexander G. Belyaev, Computer Graphcs Group, Max-Planck-Insttut für Informatk, 66123 Saarbrücken, Germany Phone: [+49](681)9325-414 Fax:

More information

High-Boost Mesh Filtering for 3-D Shape Enhancement

High-Boost Mesh Filtering for 3-D Shape Enhancement Hgh-Boost Mesh Flterng for 3-D Shape Enhancement Hrokazu Yagou Λ Alexander Belyaev y Damng We z Λ y z ; ; Shape Modelng Laboratory, Unversty of Azu, Azu-Wakamatsu 965-8580 Japan y Computer Graphcs Group,

More information

Interpolation of the Irregular Curve Network of Ship Hull Form Using Subdivision Surfaces

Interpolation of the Irregular Curve Network of Ship Hull Form Using Subdivision Surfaces 7 Interpolaton of the Irregular Curve Network of Shp Hull Form Usng Subdvson Surfaces Kyu-Yeul Lee, Doo-Yeoun Cho and Tae-Wan Km Seoul Natonal Unversty, kylee@snu.ac.kr,whendus@snu.ac.kr,taewan}@snu.ac.kr

More information

S1 Note. Basis functions.

S1 Note. Basis functions. S1 Note. Bass functons. Contents Types of bass functons...1 The Fourer bass...2 B-splne bass...3 Power and type I error rates wth dfferent numbers of bass functons...4 Table S1. Smulaton results of type

More information

Harmonic Coordinates for Character Articulation PIXAR

Harmonic Coordinates for Character Articulation PIXAR Harmonc Coordnates for Character Artculaton PIXAR Pushkar Josh Mark Meyer Tony DeRose Bran Green Tom Sanock We have a complex source mesh nsde of a smpler cage mesh We want vertex deformatons appled to

More information

Quality Improvement Algorithm for Tetrahedral Mesh Based on Optimal Delaunay Triangulation

Quality Improvement Algorithm for Tetrahedral Mesh Based on Optimal Delaunay Triangulation Intellgent Informaton Management, 013, 5, 191-195 Publshed Onlne November 013 (http://www.scrp.org/journal/m) http://dx.do.org/10.36/m.013.5601 Qualty Improvement Algorthm for Tetrahedral Mesh Based on

More information

Barycentric Coordinates. From: Mean Value Coordinates for Closed Triangular Meshes by Ju et al.

Barycentric Coordinates. From: Mean Value Coordinates for Closed Triangular Meshes by Ju et al. Barycentrc Coordnates From: Mean Value Coordnates for Closed Trangular Meshes by Ju et al. Motvaton Data nterpolaton from the vertces of a boundary polygon to ts nteror Boundary value problems Shadng Space

More information

Reading. 14. Subdivision curves. Recommended:

Reading. 14. Subdivision curves. Recommended: eadng ecommended: Stollntz, Deose, and Salesn. Wavelets for Computer Graphcs: heory and Applcatons, 996, secton 6.-6., A.5. 4. Subdvson curves Note: there s an error n Stollntz, et al., secton A.5. Equaton

More information

Smoothing Spline ANOVA for variable screening

Smoothing Spline ANOVA for variable screening Smoothng Splne ANOVA for varable screenng a useful tool for metamodels tranng and mult-objectve optmzaton L. Rcco, E. Rgon, A. Turco Outlne RSM Introducton Possble couplng Test case MOO MOO wth Game Theory

More information

Hermite Splines in Lie Groups as Products of Geodesics

Hermite Splines in Lie Groups as Products of Geodesics Hermte Splnes n Le Groups as Products of Geodescs Ethan Eade Updated May 28, 2017 1 Introducton 1.1 Goal Ths document defnes a curve n the Le group G parametrzed by tme and by structural parameters n the

More information

Support Vector Machines

Support Vector Machines /9/207 MIST.6060 Busness Intellgence and Data Mnng What are Support Vector Machnes? Support Vector Machnes Support Vector Machnes (SVMs) are supervsed learnng technques that analyze data and recognze patterns.

More information

Parallelism for Nested Loops with Non-uniform and Flow Dependences

Parallelism for Nested Loops with Non-uniform and Flow Dependences Parallelsm for Nested Loops wth Non-unform and Flow Dependences Sam-Jn Jeong Dept. of Informaton & Communcaton Engneerng, Cheonan Unversty, 5, Anseo-dong, Cheonan, Chungnam, 330-80, Korea. seong@cheonan.ac.kr

More information

Parameterization of Quadrilateral Meshes

Parameterization of Quadrilateral Meshes Parameterzaton of Quadrlateral Meshes L Lu 1, CaMng Zhang 1,, and Frank Cheng 3 1 School of Computer Scence and Technology, Shandong Unversty, Jnan, Chna Department of Computer Scence and Technology, Shandong

More information

Mesh Editing in ROI with Dual Laplacian

Mesh Editing in ROI with Dual Laplacian Mesh Edtng n ROI wth Dual Laplacan Luo Qong, Lu Bo, Ma Zhan-guo, Zhang Hong-bn College of Computer Scence, Beng Unversty of Technology, Chna lqngng@sohu.com, lubo@but.edu.cn,mzgsy@63.com,zhb@publc.bta.net.cn

More information

Ecient Computation of the Most Probable Motion from Fuzzy. Moshe Ben-Ezra Shmuel Peleg Michael Werman. The Hebrew University of Jerusalem

Ecient Computation of the Most Probable Motion from Fuzzy. Moshe Ben-Ezra Shmuel Peleg Michael Werman. The Hebrew University of Jerusalem Ecent Computaton of the Most Probable Moton from Fuzzy Correspondences Moshe Ben-Ezra Shmuel Peleg Mchael Werman Insttute of Computer Scence The Hebrew Unversty of Jerusalem 91904 Jerusalem, Israel Emal:

More information

NUMERICAL SOLVING OPTIMAL CONTROL PROBLEMS BY THE METHOD OF VARIATIONS

NUMERICAL SOLVING OPTIMAL CONTROL PROBLEMS BY THE METHOD OF VARIATIONS ARPN Journal of Engneerng and Appled Scences 006-017 Asan Research Publshng Network (ARPN). All rghts reserved. NUMERICAL SOLVING OPTIMAL CONTROL PROBLEMS BY THE METHOD OF VARIATIONS Igor Grgoryev, Svetlana

More information

Scan Conversion & Shading

Scan Conversion & Shading Scan Converson & Shadng Thomas Funkhouser Prnceton Unversty C0S 426, Fall 1999 3D Renderng Ppelne (for drect llumnaton) 3D Prmtves 3D Modelng Coordnates Modelng Transformaton 3D World Coordnates Lghtng

More information

Polyhedral Surface Smoothing with Simultaneous Mesh Regularization

Polyhedral Surface Smoothing with Simultaneous Mesh Regularization olyhedral Surface Smoothng wth Smultaneous Mesh Regularzaton Yutaka Ohtake The Unversty of Azu Azu-Wakamatsu Cty Fukushma 965-8580 Japan d800@u-azu.ac.jp Alexander G. Belyaev The Unversty of Azu Azu-Wakamatsu

More information

Scan Conversion & Shading

Scan Conversion & Shading 1 3D Renderng Ppelne (for drect llumnaton) 2 Scan Converson & Shadng Adam Fnkelsten Prnceton Unversty C0S 426, Fall 2001 3DPrmtves 3D Modelng Coordnates Modelng Transformaton 3D World Coordnates Lghtng

More information

A Binarization Algorithm specialized on Document Images and Photos

A Binarization Algorithm specialized on Document Images and Photos A Bnarzaton Algorthm specalzed on Document mages and Photos Ergna Kavalleratou Dept. of nformaton and Communcaton Systems Engneerng Unversty of the Aegean kavalleratou@aegean.gr Abstract n ths paper, a

More information

Very simple computational domains can be discretized using boundary-fitted structured meshes (also called grids)

Very simple computational domains can be discretized using boundary-fitted structured meshes (also called grids) Structured meshes Very smple computatonal domans can be dscretzed usng boundary-ftted structured meshes (also called grds) The grd lnes of a Cartesan mesh are parallel to one another Structured meshes

More information

Defense Technical Information Center Compilation Part Notice

Defense Technical Information Center Compilation Part Notice UNCLASSIFIED Defense Technical Information Center Compilation Part Notice ADP012048 TITLE: Discrete Fairing of Curves and Surfaces Based on Linear Curvature Distribution DISTRIBUTION: Approved for public

More information

Modeling, Manipulating, and Visualizing Continuous Volumetric Data: A Novel Spline-based Approach

Modeling, Manipulating, and Visualizing Continuous Volumetric Data: A Novel Spline-based Approach Modelng, Manpulatng, and Vsualzng Contnuous Volumetrc Data: A Novel Splne-based Approach Jng Hua Center for Vsual Computng, Department of Computer Scence SUNY at Stony Brook Talk Outlne Introducton and

More information

A Five-Point Subdivision Scheme with Two Parameters and a Four-Point Shape-Preserving Scheme

A Five-Point Subdivision Scheme with Two Parameters and a Four-Point Shape-Preserving Scheme Mathematcal and Computatonal Applcatons Artcle A Fve-Pont Subdvson Scheme wth Two Parameters and a Four-Pont Shape-Preservng Scheme Jeqng Tan,2, Bo Wang, * and Jun Sh School of Mathematcs, Hefe Unversty

More information

Active Contours/Snakes

Active Contours/Snakes Actve Contours/Snakes Erkut Erdem Acknowledgement: The sldes are adapted from the sldes prepared by K. Grauman of Unversty of Texas at Austn Fttng: Edges vs. boundares Edges useful sgnal to ndcate occludng

More information

2x x l. Module 3: Element Properties Lecture 4: Lagrange and Serendipity Elements

2x x l. Module 3: Element Properties Lecture 4: Lagrange and Serendipity Elements Module 3: Element Propertes Lecture : Lagrange and Serendpty Elements 5 In last lecture note, the nterpolaton functons are derved on the bass of assumed polynomal from Pascal s trangle for the fled varable.

More information

6.854 Advanced Algorithms Petar Maymounkov Problem Set 11 (November 23, 2005) With: Benjamin Rossman, Oren Weimann, and Pouya Kheradpour

6.854 Advanced Algorithms Petar Maymounkov Problem Set 11 (November 23, 2005) With: Benjamin Rossman, Oren Weimann, and Pouya Kheradpour 6.854 Advanced Algorthms Petar Maymounkov Problem Set 11 (November 23, 2005) Wth: Benjamn Rossman, Oren Wemann, and Pouya Kheradpour Problem 1. We reduce vertex cover to MAX-SAT wth weghts, such that the

More information

A MOVING MESH APPROACH FOR SIMULATION BUDGET ALLOCATION ON CONTINUOUS DOMAINS

A MOVING MESH APPROACH FOR SIMULATION BUDGET ALLOCATION ON CONTINUOUS DOMAINS Proceedngs of the Wnter Smulaton Conference M E Kuhl, N M Steger, F B Armstrong, and J A Jones, eds A MOVING MESH APPROACH FOR SIMULATION BUDGET ALLOCATION ON CONTINUOUS DOMAINS Mark W Brantley Chun-Hung

More information

Chapter 6 Programmng the fnte element method Inow turn to the man subject of ths book: The mplementaton of the fnte element algorthm n computer programs. In order to make my dscusson as straghtforward

More information

R s s f. m y s. SPH3UW Unit 7.3 Spherical Concave Mirrors Page 1 of 12. Notes

R s s f. m y s. SPH3UW Unit 7.3 Spherical Concave Mirrors Page 1 of 12. Notes SPH3UW Unt 7.3 Sphercal Concave Mrrors Page 1 of 1 Notes Physcs Tool box Concave Mrror If the reflectng surface takes place on the nner surface of the sphercal shape so that the centre of the mrror bulges

More information

A Newton-Type Method for Constrained Least-Squares Data-Fitting with Easy-to-Control Rational Curves

A Newton-Type Method for Constrained Least-Squares Data-Fitting with Easy-to-Control Rational Curves A Newton-Type Method for Constraned Least-Squares Data-Fttng wth Easy-to-Control Ratonal Curves G. Cascola a, L. Roman b, a Department of Mathematcs, Unversty of Bologna, P.zza d Porta San Donato 5, 4017

More information

Computer Animation and Visualisation. Lecture 4. Rigging / Skinning

Computer Animation and Visualisation. Lecture 4. Rigging / Skinning Computer Anmaton and Vsualsaton Lecture 4. Rggng / Sknnng Taku Komura Overvew Sknnng / Rggng Background knowledge Lnear Blendng How to decde weghts? Example-based Method Anatomcal models Sknnng Assume

More information

Type-2 Fuzzy Non-uniform Rational B-spline Model with Type-2 Fuzzy Data

Type-2 Fuzzy Non-uniform Rational B-spline Model with Type-2 Fuzzy Data Malaysan Journal of Mathematcal Scences 11(S) Aprl : 35 46 (2017) Specal Issue: The 2nd Internatonal Conference and Workshop on Mathematcal Analyss (ICWOMA 2016) MALAYSIAN JOURNAL OF MATHEMATICAL SCIENCES

More information

GSLM Operations Research II Fall 13/14

GSLM Operations Research II Fall 13/14 GSLM 58 Operatons Research II Fall /4 6. Separable Programmng Consder a general NLP mn f(x) s.t. g j (x) b j j =. m. Defnton 6.. The NLP s a separable program f ts objectve functon and all constrants are

More information

Modelling of curves and surfaces in polar. and Cartesian coordinates. G.Casciola and S.Morigi. Department of Mathematics, University of Bologna, Italy

Modelling of curves and surfaces in polar. and Cartesian coordinates. G.Casciola and S.Morigi. Department of Mathematics, University of Bologna, Italy Modellng of curves and surfaces n polar and Cartesan coordnates G.Cascola and S.Morg Department of Mathematcs, Unversty of Bologna, Italy Abstract A new class of splne curves n polar coordnates has been

More information

Mathematics 256 a course in differential equations for engineering students

Mathematics 256 a course in differential equations for engineering students Mathematcs 56 a course n dfferental equatons for engneerng students Chapter 5. More effcent methods of numercal soluton Euler s method s qute neffcent. Because the error s essentally proportonal to the

More information

A Fast Visual Tracking Algorithm Based on Circle Pixels Matching

A Fast Visual Tracking Algorithm Based on Circle Pixels Matching A Fast Vsual Trackng Algorthm Based on Crcle Pxels Matchng Zhqang Hou hou_zhq@sohu.com Chongzhao Han czhan@mal.xjtu.edu.cn Ln Zheng Abstract: A fast vsual trackng algorthm based on crcle pxels matchng

More information

Improvement of Spatial Resolution Using BlockMatching Based Motion Estimation and Frame. Integration

Improvement of Spatial Resolution Using BlockMatching Based Motion Estimation and Frame. Integration Improvement of Spatal Resoluton Usng BlockMatchng Based Moton Estmaton and Frame Integraton Danya Suga and Takayuk Hamamoto Graduate School of Engneerng, Tokyo Unversty of Scence, 6-3-1, Nuku, Katsuska-ku,

More information

An Optimal Algorithm for Prufer Codes *

An Optimal Algorithm for Prufer Codes * J. Software Engneerng & Applcatons, 2009, 2: 111-115 do:10.4236/jsea.2009.22016 Publshed Onlne July 2009 (www.scrp.org/journal/jsea) An Optmal Algorthm for Prufer Codes * Xaodong Wang 1, 2, Le Wang 3,

More information

Determining the Optimal Bandwidth Based on Multi-criterion Fusion

Determining the Optimal Bandwidth Based on Multi-criterion Fusion Proceedngs of 01 4th Internatonal Conference on Machne Learnng and Computng IPCSIT vol. 5 (01) (01) IACSIT Press, Sngapore Determnng the Optmal Bandwdth Based on Mult-crteron Fuson Ha-L Lang 1+, Xan-Mn

More information

Smooth Approximation to Surface Meshes of Arbitrary Topology with Locally Blended Radial Basis Functions

Smooth Approximation to Surface Meshes of Arbitrary Topology with Locally Blended Radial Basis Functions 587 Smooth Approxmaton to Surface eshes of Arbtrary Topology wth Locally Blended Radal Bass Functons ngyong Pang 1,, Weyn a 1, Zhgeng Pan and Fuyan Zhang 1 Cty Unversty of Hong Kong, mewma@ctyu.edu.hk

More information

Multiblock method for database generation in finite element programs

Multiblock method for database generation in finite element programs Proc. of the 9th WSEAS Int. Conf. on Mathematcal Methods and Computatonal Technques n Electrcal Engneerng, Arcachon, October 13-15, 2007 53 Multblock method for database generaton n fnte element programs

More information

Review of approximation techniques

Review of approximation techniques CHAPTER 2 Revew of appromaton technques 2. Introducton Optmzaton problems n engneerng desgn are characterzed by the followng assocated features: the objectve functon and constrants are mplct functons evaluated

More information

G 2 Surface Modeling Using Minimal Mean-Curvature-Variation Flow

G 2 Surface Modeling Using Minimal Mean-Curvature-Variation Flow G 2 Surface Modelng Usng Mnmal Mean-Curvature-Varaton Flow Guolang Xu 1 Qn Zhang 2 1,2 LSEC, Insttute of Computatonal Mathematcs, Academy of Mathematcs and System Scences, Chnese Academy of Scences, Bejng

More information

Solitary and Traveling Wave Solutions to a Model. of Long Range Diffusion Involving Flux with. Stability Analysis

Solitary and Traveling Wave Solutions to a Model. of Long Range Diffusion Involving Flux with. Stability Analysis Internatonal Mathematcal Forum, Vol. 6,, no. 7, 8 Soltary and Travelng Wave Solutons to a Model of Long Range ffuson Involvng Flux wth Stablty Analyss Manar A. Al-Qudah Math epartment, Rabgh Faculty of

More information

Problem Set 3 Solutions

Problem Set 3 Solutions Introducton to Algorthms October 4, 2002 Massachusetts Insttute of Technology 6046J/18410J Professors Erk Demane and Shaf Goldwasser Handout 14 Problem Set 3 Solutons (Exercses were not to be turned n,

More information

Lecture 5: Multilayer Perceptrons

Lecture 5: Multilayer Perceptrons Lecture 5: Multlayer Perceptrons Roger Grosse 1 Introducton So far, we ve only talked about lnear models: lnear regresson and lnear bnary classfers. We noted that there are functons that can t be represented

More information

Fitting: Deformable contours April 26 th, 2018

Fitting: Deformable contours April 26 th, 2018 4/6/08 Fttng: Deformable contours Aprl 6 th, 08 Yong Jae Lee UC Davs Recap so far: Groupng and Fttng Goal: move from array of pxel values (or flter outputs) to a collecton of regons, objects, and shapes.

More information

Discrete surface modelling using partial differential equations

Discrete surface modelling using partial differential equations Computer Aded Geometrc Desgn 23 (2006) 125 145 www.elsever.com/locate/cagd Dscrete surface modellng usng partal dfferental equatons Guolang Xu a,1,qngpan a, Chandrajt L. Bajaj b,,2 a State Key Laboratory

More information

LECTURE : MANIFOLD LEARNING

LECTURE : MANIFOLD LEARNING LECTURE : MANIFOLD LEARNING Rta Osadchy Some sldes are due to L.Saul, V. C. Raykar, N. Verma Topcs PCA MDS IsoMap LLE EgenMaps Done! Dmensonalty Reducton Data representaton Inputs are real-valued vectors

More information

Support Vector Machines. CS534 - Machine Learning

Support Vector Machines. CS534 - Machine Learning Support Vector Machnes CS534 - Machne Learnng Perceptron Revsted: Lnear Separators Bnar classfcaton can be veed as the task of separatng classes n feature space: b > 0 b 0 b < 0 f() sgn( b) Lnear Separators

More information

Programming in Fortran 90 : 2017/2018

Programming in Fortran 90 : 2017/2018 Programmng n Fortran 90 : 2017/2018 Programmng n Fortran 90 : 2017/2018 Exercse 1 : Evaluaton of functon dependng on nput Wrte a program who evaluate the functon f (x,y) for any two user specfed values

More information

Image Representation & Visualization Basic Imaging Algorithms Shape Representation and Analysis. outline

Image Representation & Visualization Basic Imaging Algorithms Shape Representation and Analysis. outline mage Vsualzaton mage Vsualzaton mage Representaton & Vsualzaton Basc magng Algorthms Shape Representaton and Analyss outlne mage Representaton & Vsualzaton Basc magng Algorthms Shape Representaton and

More information

An Accurate Evaluation of Integrals in Convex and Non convex Polygonal Domain by Twelve Node Quadrilateral Finite Element Method

An Accurate Evaluation of Integrals in Convex and Non convex Polygonal Domain by Twelve Node Quadrilateral Finite Element Method Internatonal Journal of Computatonal and Appled Mathematcs. ISSN 89-4966 Volume, Number (07), pp. 33-4 Research Inda Publcatons http://www.rpublcaton.com An Accurate Evaluaton of Integrals n Convex and

More information

Complex Numbers. Now we also saw that if a and b were both positive then ab = a b. For a second let s forget that restriction and do the following.

Complex Numbers. Now we also saw that if a and b were both positive then ab = a b. For a second let s forget that restriction and do the following. Complex Numbers The last topc n ths secton s not really related to most of what we ve done n ths chapter, although t s somewhat related to the radcals secton as we wll see. We also won t need the materal

More information

An Entropy-Based Approach to Integrated Information Needs Assessment

An Entropy-Based Approach to Integrated Information Needs Assessment Dstrbuton Statement A: Approved for publc release; dstrbuton s unlmted. An Entropy-Based Approach to ntegrated nformaton Needs Assessment June 8, 2004 Wllam J. Farrell Lockheed Martn Advanced Technology

More information

A Unified, Integral Construction For Coordinates Over Closed Curves

A Unified, Integral Construction For Coordinates Over Closed Curves A Unfed, Integral Constructon For Coordnates Over Closed Curves Schaefer S., Ju T. and Warren J. Abstract We propose a smple generalzaton of Shephard s nterpolaton to pecewse smooth, convex closed curves

More information

Wavefront Reconstructor

Wavefront Reconstructor A Dstrbuted Smplex B-Splne Based Wavefront Reconstructor Coen de Vsser and Mchel Verhaegen 14-12-201212 2012 Delft Unversty of Technology Contents Introducton Wavefront reconstructon usng Smplex B-Splnes

More information

Accounting for the Use of Different Length Scale Factors in x, y and z Directions

Accounting for the Use of Different Length Scale Factors in x, y and z Directions 1 Accountng for the Use of Dfferent Length Scale Factors n x, y and z Drectons Taha Soch (taha.soch@kcl.ac.uk) Imagng Scences & Bomedcal Engneerng, Kng s College London, The Rayne Insttute, St Thomas Hosptal,

More information

Compiler Design. Spring Register Allocation. Sample Exercises and Solutions. Prof. Pedro C. Diniz

Compiler Design. Spring Register Allocation. Sample Exercises and Solutions. Prof. Pedro C. Diniz Compler Desgn Sprng 2014 Regster Allocaton Sample Exercses and Solutons Prof. Pedro C. Dnz USC / Informaton Scences Insttute 4676 Admralty Way, Sute 1001 Marna del Rey, Calforna 90292 pedro@s.edu Regster

More information

Vectorization of Image Outlines Using Rational Spline and Genetic Algorithm

Vectorization of Image Outlines Using Rational Spline and Genetic Algorithm 01 Internatonal Conference on Image, Vson and Computng (ICIVC 01) IPCSIT vol. 50 (01) (01) IACSIT Press, Sngapore DOI: 10.776/IPCSIT.01.V50.4 Vectorzaton of Image Outlnes Usng Ratonal Splne and Genetc

More information

Explicit Formulas and Efficient Algorithm for Moment Computation of Coupled RC Trees with Lumped and Distributed Elements

Explicit Formulas and Efficient Algorithm for Moment Computation of Coupled RC Trees with Lumped and Distributed Elements Explct Formulas and Effcent Algorthm for Moment Computaton of Coupled RC Trees wth Lumped and Dstrbuted Elements Qngan Yu and Ernest S.Kuh Electroncs Research Lab. Unv. of Calforna at Berkeley Berkeley

More information

Parallel matrix-vector multiplication

Parallel matrix-vector multiplication Appendx A Parallel matrx-vector multplcaton The reduced transton matrx of the three-dmensonal cage model for gel electrophoress, descrbed n secton 3.2, becomes excessvely large for polymer lengths more

More information

A Geometric Approach for Multi-Degree Spline

A Geometric Approach for Multi-Degree Spline L X, Huang ZJ, Lu Z. A geometrc approach for mult-degree splne. JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY 27(4): 84 850 July 202. DOI 0.007/s390-02-268-2 A Geometrc Approach for Mult-Degree Splne Xn L

More information

Analysis of Continuous Beams in General

Analysis of Continuous Beams in General Analyss of Contnuous Beams n General Contnuous beams consdered here are prsmatc, rgdly connected to each beam segment and supported at varous ponts along the beam. onts are selected at ponts of support,

More information

Parallel Numerics. 1 Preconditioning & Iterative Solvers (From 2016)

Parallel Numerics. 1 Preconditioning & Iterative Solvers (From 2016) Technsche Unverstät München WSe 6/7 Insttut für Informatk Prof. Dr. Thomas Huckle Dpl.-Math. Benjamn Uekermann Parallel Numercs Exercse : Prevous Exam Questons Precondtonng & Iteratve Solvers (From 6)

More information

Simulation Based Analysis of FAST TCP using OMNET++

Simulation Based Analysis of FAST TCP using OMNET++ Smulaton Based Analyss of FAST TCP usng OMNET++ Umar ul Hassan 04030038@lums.edu.pk Md Term Report CS678 Topcs n Internet Research Sprng, 2006 Introducton Internet traffc s doublng roughly every 3 months

More information

Chapter 1. Comparison of an O(N ) and an O(N log N ) N -body solver. Abstract

Chapter 1. Comparison of an O(N ) and an O(N log N ) N -body solver. Abstract Chapter 1 Comparson of an O(N ) and an O(N log N ) N -body solver Gavn J. Prngle Abstract In ths paper we compare the performance characterstcs of two 3-dmensonal herarchcal N-body solvers an O(N) and

More information

The Greedy Method. Outline and Reading. Change Money Problem. Greedy Algorithms. Applications of the Greedy Strategy. The Greedy Method Technique

The Greedy Method. Outline and Reading. Change Money Problem. Greedy Algorithms. Applications of the Greedy Strategy. The Greedy Method Technique //00 :0 AM Outlne and Readng The Greedy Method The Greedy Method Technque (secton.) Fractonal Knapsack Problem (secton..) Task Schedulng (secton..) Mnmum Spannng Trees (secton.) Change Money Problem Greedy

More information

An Application of the Dulmage-Mendelsohn Decomposition to Sparse Null Space Bases of Full Row Rank Matrices

An Application of the Dulmage-Mendelsohn Decomposition to Sparse Null Space Bases of Full Row Rank Matrices Internatonal Mathematcal Forum, Vol 7, 2012, no 52, 2549-2554 An Applcaton of the Dulmage-Mendelsohn Decomposton to Sparse Null Space Bases of Full Row Rank Matrces Mostafa Khorramzadeh Department of Mathematcal

More information

Journal of Computational Physics

Journal of Computational Physics Journal of Computatonal Physcs 230 (2011) 2540 2561 Contents lsts avalable at ScenceDrect Journal of Computatonal Physcs journal homepage: www.elsever.com/locate/jcp A grd based partcle method for solvng

More information

Discrete Schemes for Gaussian Curvature and Their Convergence

Discrete Schemes for Gaussian Curvature and Their Convergence Dscrete Schemes for Gaussan Curvature and Ther Convergence Zhqang Xu Guolang Xu Insttute of Computatonal Math. and Sc. and Eng. Computng, Academy of Mathematcs and System Scences, Chnese Academy of Scences,

More information

Feature Reduction and Selection

Feature Reduction and Selection Feature Reducton and Selecton Dr. Shuang LIANG School of Software Engneerng TongJ Unversty Fall, 2012 Today s Topcs Introducton Problems of Dmensonalty Feature Reducton Statstc methods Prncpal Components

More information

n i P i φ i t i P i-1 i+1 P i+1 P i i-1 i+1 2 r i

n i P i φ i t i P i-1 i+1 P i+1 P i i-1 i+1 2 r i New Algorthms for Controllng Actve Contours Shape and Topology H. Delngette and J. Montagnat Projet Epdaure I.N.R.I.A. 06902 Sopha-Antpols Cedex, BP 93, France Abstract In recent years, the eld of actve-contour

More information

Load Balancing for Hex-Cell Interconnection Network

Load Balancing for Hex-Cell Interconnection Network Int. J. Communcatons, Network and System Scences,,, - Publshed Onlne Aprl n ScRes. http://www.scrp.org/journal/jcns http://dx.do.org/./jcns.. Load Balancng for Hex-Cell Interconnecton Network Saher Manaseer,

More information

Classification / Regression Support Vector Machines

Classification / Regression Support Vector Machines Classfcaton / Regresson Support Vector Machnes Jeff Howbert Introducton to Machne Learnng Wnter 04 Topcs SVM classfers for lnearly separable classes SVM classfers for non-lnearly separable classes SVM

More information

Research Article Quasi-Bézier Curves with Shape Parameters

Research Article Quasi-Bézier Curves with Shape Parameters Hndaw Publshng Corporaton Appled Mathematcs Volume 3, Artcle ID 739, 9 pages http://dxdoorg/55/3/739 Research Artcle Quas-Bézer Curves wth Shape Parameters Jun Chen Faculty of Scence, Nngbo Unversty of

More information

Preconditioning Parallel Sparse Iterative Solvers for Circuit Simulation

Preconditioning Parallel Sparse Iterative Solvers for Circuit Simulation Precondtonng Parallel Sparse Iteratve Solvers for Crcut Smulaton A. Basermann, U. Jaekel, and K. Hachya 1 Introducton One mportant mathematcal problem n smulaton of large electrcal crcuts s the soluton

More information

Computer Graphics. - Spline and Subdivision Surfaces - Hendrik Lensch. Computer Graphics WS07/08 Spline & Subdivision Surfaces

Computer Graphics. - Spline and Subdivision Surfaces - Hendrik Lensch. Computer Graphics WS07/08 Spline & Subdivision Surfaces Computer Graphcs - Splne and Subdvson Surfaces - Hendrk Lensch Overvew Last Tme Image-Based Renderng Today Parametrc Curves Lagrange Interpolaton Hermte Splnes Bezer Splnes DeCasteljau Algorthm Parameterzaton

More information

Helsinki University Of Technology, Systems Analysis Laboratory Mat Independent research projects in applied mathematics (3 cr)

Helsinki University Of Technology, Systems Analysis Laboratory Mat Independent research projects in applied mathematics (3 cr) Helsnk Unversty Of Technology, Systems Analyss Laboratory Mat-2.08 Independent research projects n appled mathematcs (3 cr) "! #$&% Antt Laukkanen 506 R ajlaukka@cc.hut.f 2 Introducton...3 2 Multattrbute

More information

Course Introduction. Algorithm 8/31/2017. COSC 320 Advanced Data Structures and Algorithms. COSC 320 Advanced Data Structures and Algorithms

Course Introduction. Algorithm 8/31/2017. COSC 320 Advanced Data Structures and Algorithms. COSC 320 Advanced Data Structures and Algorithms Course Introducton Course Topcs Exams, abs, Proects A quc loo at a few algorthms 1 Advanced Data Structures and Algorthms Descrpton: We are gong to dscuss algorthm complexty analyss, algorthm desgn technques

More information

Learning the Kernel Parameters in Kernel Minimum Distance Classifier

Learning the Kernel Parameters in Kernel Minimum Distance Classifier Learnng the Kernel Parameters n Kernel Mnmum Dstance Classfer Daoqang Zhang 1,, Songcan Chen and Zh-Hua Zhou 1* 1 Natonal Laboratory for Novel Software Technology Nanjng Unversty, Nanjng 193, Chna Department

More information

An Approach in Coloring Semi-Regular Tilings on the Hyperbolic Plane

An Approach in Coloring Semi-Regular Tilings on the Hyperbolic Plane An Approach n Colorng Sem-Regular Tlngs on the Hyperbolc Plane Ma Louse Antonette N De Las Peñas, mlp@mathscmathadmueduph Glenn R Lago, glago@yahoocom Math Department, Ateneo de Manla Unversty, Loyola

More information

NAG Fortran Library Chapter Introduction. G10 Smoothing in Statistics

NAG Fortran Library Chapter Introduction. G10 Smoothing in Statistics Introducton G10 NAG Fortran Lbrary Chapter Introducton G10 Smoothng n Statstcs Contents 1 Scope of the Chapter... 2 2 Background to the Problems... 2 2.1 Smoothng Methods... 2 2.2 Smoothng Splnes and Regresson

More information

S.P.H. : A SOLUTION TO AVOID USING EROSION CRITERION?

S.P.H. : A SOLUTION TO AVOID USING EROSION CRITERION? S.P.H. : A SOLUTION TO AVOID USING EROSION CRITERION? Célne GALLET ENSICA 1 place Emle Bloun 31056 TOULOUSE CEDEX e-mal :cgallet@ensca.fr Jean Luc LACOME DYNALIS Immeuble AEROPOLE - Bat 1 5, Avenue Albert

More information

Edge Detection in Noisy Images Using the Support Vector Machines

Edge Detection in Noisy Images Using the Support Vector Machines Edge Detecton n Nosy Images Usng the Support Vector Machnes Hlaro Gómez-Moreno, Saturnno Maldonado-Bascón, Francsco López-Ferreras Sgnal Theory and Communcatons Department. Unversty of Alcalá Crta. Madrd-Barcelona

More information

Feature-Preserving Mesh Denoising via Bilateral Normal Filtering

Feature-Preserving Mesh Denoising via Bilateral Normal Filtering Feature-Preservng Mesh Denosng va Blateral Normal Flterng Ka-Wah Lee, Wen-Png Wang Computer Graphcs Group Department of Computer Scence, The Unversty of Hong Kong kwlee@cs.hku.hk, wenpng@cs.hku.hk Abstract

More information

Discrete Smooth Interpolation: Constrained Discrete Fairing for Arbitrary Meshes

Discrete Smooth Interpolation: Constrained Discrete Fairing for Arbitrary Meshes Dscrete Smooth Interpolaton: Constraned Dscrete Farng for rbtrary Meshes runo Lévy Jean-Laurent Mallet IS-GOCD (Inra Lorrane/CNRS ENSG, rue du doyen Marcel Roubeault, 54500 Vandoeuvre bstract In ths paper,

More information

Injective Shape Deformations Using Cube-Like Cages

Injective Shape Deformations Using Cube-Like Cages 309 Injectve Shape Deformatons Usng Cube-Lke Cages Jr Kosnka 1 and Mchael Barton 2 1 Unversty of Oslo, jr.kosnka@cma.uo.no 2 Technon, barton@cs.technon.ac.l ABSTRACT The present paper nvestgates an applcaton

More information

Constructing Minimum Connected Dominating Set: Algorithmic approach

Constructing Minimum Connected Dominating Set: Algorithmic approach Constructng Mnmum Connected Domnatng Set: Algorthmc approach G.N. Puroht and Usha Sharma Centre for Mathematcal Scences, Banasthal Unversty, Rajasthan 304022 usha.sharma94@yahoo.com Abstract: Connected

More information

Yair Weiss. Dept. of Brain and Cognitive Sciences. Massachusetts Institute of Technology. Abstract

Yair Weiss. Dept. of Brain and Cognitive Sciences. Massachusetts Institute of Technology. Abstract n: M.C. Mozer, M.I. Jordan and T. Petsche, edtors, Advances n Neural Informaton Processng Systems 9 908-95 (997). Interpretng mages by propagatng Bayesan belefs Yar Wess Dept. of Bran and Cogntve Scences

More information

Robust Curvature Estimation and Geometry Analysis of 3D point Cloud Surfaces

Robust Curvature Estimation and Geometry Analysis of 3D point Cloud Surfaces Robust Curvature Estmaton and Geometry Analyss of 3D pont Cloud Surfaces Xaopeng ZHANG, Hongjun LI, Zhangln CHENG, Ykuan ZHANG Sno-French Laboratory LIAMA, Insttute of Automaton, CAS, Bejng 100190, Chna

More information

Adaptive Fairing of Surface Meshes by Geometric Diffusion

Adaptive Fairing of Surface Meshes by Geometric Diffusion Adaptve Farng of Surface Meshes by Geometrc Dffuson Chandrajt L. Bajaj Department of Computer Scences, Unversty of Texas, Austn, TX 78712 Emal: bajaj@cs.utexas.edu Guolang Xu State Key Lab. of Scentfc

More information

Simplification of 3D Meshes

Simplification of 3D Meshes Smplfcaton of 3D Meshes Addy Ngan /4/00 Outlne Motvaton Taxonomy of smplfcaton methods Hoppe et al, Mesh optmzaton Hoppe, Progressve meshes Smplfcaton of 3D Meshes 1 Motvaton Hgh detaled meshes becomng

More information

An Iterative Solution Approach to Process Plant Layout using Mixed Integer Optimisation

An Iterative Solution Approach to Process Plant Layout using Mixed Integer Optimisation 17 th European Symposum on Computer Aded Process Engneerng ESCAPE17 V. Plesu and P.S. Agach (Edtors) 2007 Elsever B.V. All rghts reserved. 1 An Iteratve Soluton Approach to Process Plant Layout usng Mxed

More information

CS 534: Computer Vision Model Fitting

CS 534: Computer Vision Model Fitting CS 534: Computer Vson Model Fttng Sprng 004 Ahmed Elgammal Dept of Computer Scence CS 534 Model Fttng - 1 Outlnes Model fttng s mportant Least-squares fttng Maxmum lkelhood estmaton MAP estmaton Robust

More information

5 The Primal-Dual Method

5 The Primal-Dual Method 5 The Prmal-Dual Method Orgnally desgned as a method for solvng lnear programs, where t reduces weghted optmzaton problems to smpler combnatoral ones, the prmal-dual method (PDM) has receved much attenton

More information

Some Tutorial about the Project. Computer Graphics

Some Tutorial about the Project. Computer Graphics Some Tutoral about the Project Lecture 6 Rastersaton, Antalasng, Texture Mappng, I have already covered all the topcs needed to fnsh the 1 st practcal Today, I wll brefly explan how to start workng on

More information

Abstract Ths paper ponts out an mportant source of necency n Smola and Scholkopf's Sequental Mnmal Optmzaton (SMO) algorthm for SVM regresson that s c

Abstract Ths paper ponts out an mportant source of necency n Smola and Scholkopf's Sequental Mnmal Optmzaton (SMO) algorthm for SVM regresson that s c Improvements to SMO Algorthm for SVM Regresson 1 S.K. Shevade S.S. Keerth C. Bhattacharyya & K.R.K. Murthy shrsh@csa.sc.ernet.n mpessk@guppy.mpe.nus.edu.sg cbchru@csa.sc.ernet.n murthy@csa.sc.ernet.n 1

More information

THE PULL-PUSH ALGORITHM REVISITED

THE PULL-PUSH ALGORITHM REVISITED THE PULL-PUSH ALGORITHM REVISITED Improvements, Computaton of Pont Denstes, and GPU Implementaton Martn Kraus Computer Graphcs & Vsualzaton Group, Technsche Unverstät München, Boltzmannstraße 3, 85748

More information