Computing depth maps from descent images

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1 Machne Vson and Applcatons (005) Dgtal Object Identfer (DOI) 0.007/s Machne Vson and Applcatons Computng depth maps from descent mages Yaln Xong, Clark F. Olson, Larry H. Matthes 3 KLA-Tencor, 60 Ro Robles St., San Jose, CA 9534, USA Unversty of Washngton, Computng and Software Systems, 85 Campus Way NE, Box , Bothell, WA 980, USA 3 Jet Propulson Laboratory, Calforna Insttute of Technology, 4800 Oak Grove Drve, M/S 5-09, Pasadena, CA 909, USA Receved: 7 November 00 / Accepted: 3 September 004 Publshed onlne: 5 February 005 c Sprnger-Verlag 005 Abstract. In the exploraton of the planets of our solar system, mages taken durng a lander s descent to the surface of a planet provde a crtcal lnk between orbtal mages and surface mages. The descent mages not only allow us to locate the landng ste n a global coordnate frame, but they also provde progressvely hgher-resoluton maps for msson plannng. Ths paper addresses the generaton of depth maps from the descent mages. Our approach has two steps, moton refnement and depth recovery. Durng moton refnement, we use an ntal moton estmate n order to avod the ntrnsc moton ambguty. The objectve of the moton-refnement step s to adjust the moton parameters such that the reprojecton error s mnmzed. The depth-recovery step correlates adjacent frames to match pxels for trangulaton. Due to the descendng moton, the conventonal rectfcaton process s replaced by a set of ant-alasng mage warpngs correspondng to a set of vrtual parallel planes. We demonstrate expermental results on synthetc and real descent mages. Keywords: Planetary exploraton Structure from moton Descent mages Moton estmaton Terran mappng Introducton Future space mssons that land on Mars (and other planetary bodes) may nclude a downward-lookng camera mounted on the vehcle as t descends to the surface. Images taken by such a camera durng the descent provde a crtcal lnk between orbtal mages and lander/rover mages on the surface of the planet. By matchng the descent mages aganst orbtal mages, the descent vehcle can localze tself n global coordnates and, therefore, acheve precson landng. Through analyss of the descent mages, we can buld a multresoluton terran map for safe landng, rover plannng, navgaton, and localzaton. Ths paper addresses the ssue of generatng Correspondence to: Clark F. Olson (e-mal: cfolson@u.washngton.edu, Tel.: , Fax: ) multresoluton terran maps from a sequence of descent mages. We use moton-estmaton and structure-from-moton technques to recover depth maps from the mages. A new technque for computng depths s descrbed that s based on correlatng the mages after performng ant-alasng mage warpngs that correspond to a set of vrtual planar surfaces. It s well known that, when the vewed terran s a planar surface, the moton-recovery problem s ll-posed, snce translatons parallel to the surface appear smlar to rotatons about axes parallel to the surface. Moton recovery s, therefore, not generally relable for ths scenaro. However, f we have an ndependent means to measure the orentaton of the camera, we can obtan stable moton recovery. For planetary exploraton mssons, such measurements can be provded by the nertal navgaton sensors on the landng spacecraft. For space mssons, t s lkely that the moton wll be nearly perpendcular to the planetary surface. For the Mars Polar Lander msson, whch was unable to return data due to loss of the lander, t was planned that the camera would take an mage every tme the dstance to the ground halved. In other words, there would be roughly a scale factor of two between adjacent frames n the sequence. A smlar scenaro s lkely n future mssons. The large change of scale prohbts us from trackng many features across several frames. For most features, we lmt our correlaton and depth recovery to adjacent frames for ths reason. The descendng moton also causes problems n correlatng the mages. Snce the eppoles are located near the center of the mages, t s not practcal to rectfy adjacent frames n the same manner that tradtonal stereo technques do. Instead, we perform a vrtual rectfcaton, resamplng the mages by consderng a set of parallel planar surfaces through the terran. Each surface corresponds to a projectve warpng between the adjacent mages. The surface that yelds the best correlaton at each pxel determnes the depth estmate for that locaton. Ths methodology not only algns mages accordng to the eppolar lnes but also equalzes the mage scales usng ant-alased warpngs. Of course, many other approaches have been proposed for recoverng moton and depth from mage sequences [,4,6,8,,4]. Ths work dffers from most prevous work n two ways. Frst, almost all of the moton s forward along

2 Yaln Xong et al.: Computng depth maps from descent mages I I Terran Fg.. Descent moton the camera pontng drecton. Second, large movements n the camera poston occur between frames, usually doublng the resoluton of the mages at each frame. Ths work s thus n part, an applcaton of prevous work to the problem of mappng spacecraft descent magery and, n part, new technques for dealng wth the above problems. The technque produces dense maps of the terran and operates under the full perspectve projecton. In the next two sectons, we descrbe the motonrefnement and depth-recovery steps n detal. We then dscuss our experments on synthetc and real descent mages. The results demonstrate the varous terran features that can be recovered. Near the landng ste, small obstacles such as rocks and gulles can be dentfed for plannng local rover navgaton. Further from the landng ste, larger features such as mountan slopes and clffs are vsble for use n long-range plannng. Moton refnement Recoverng camera moton from two or more frames s one of the classcal problems n computer vson. Lnear [7] and nonlnear [3] solutons have been proposed. Our scenaro nvolves a downward moton towards a roughly planar surface (as n Fg. ). Generc moton recovery from matched features s ll-posed owng to a numercal sngularty (rotatons and translatons are dffcult to dstngush.) Snce the camera can be rgdly attached to the lander, and the change n the lander orentaton can be measured accurately by an nertal navgaton system onboard, we can elmnate the sngularty problem by addng a penalty term for devatng from the measured orentaton. The followng two subsectons brefly explan our feature correspondence and nonlnear optmzaton for moton refnement.. Feature correspondence For each par of adjacent frames n the sequence, we determne correspondences for features that have been selected n the hgher-resoluton frame nto the lower-resoluton frame. Forstner s nterest operator [3] s used to evaluate the dstnctveness of the features n the hgher-resoluton frame. We select the features wth hgh scores whle dsallowng features that are too close together (Fg. a). a b Fg. a,b. Feature correspondence between adjacent frames. a Selected features. b Correspondences detected Once the mage resolutons have been equalzed (usng downsamplng or ant-alasng warpng, f necessary), feature correspondence can be determned n a straghtforward manner. For every feature n the reference mage, we search an area n the target mage for a match. The locaton of the search area s derved from the ntal estmate of the vehcle ego-moton and ts alttude. The ntal estmates do not need to be precse. The sze of the search area s determned by how uncertan the ntal estmates are. Once the search area s located, we detect the feature match through normalzed correlaton.. Nonlnear moton estmaton The objectve of moton refnement s to establsh the precse camera moton between two adjacent frames such that the eppolar constrants are satsfed to subpxel accuracy. It s unrealstc to expect the onboard nertal sensors to track the camera orentaton wth such precson. It s therefore crucal to be able to refne the moton parameters pror to recoverng the depth map. The matched features provde a rch set of observatons to constran the camera moton, even though the relatonshp between the locatons of the matched features and the camera moton parameters s nonlnear. Let us assume that the projecton matrx of the camera (ncludng the calbrated nternal parameters) s A, the locaton of feature at tme t s [X t,yt,zt ]T n the camera frame of reference, ts mage locaton at tme t represented n homogeneous coordnates s

3 Yaln Xong et al.: Computng depth maps from descent mages [x t,yt,zt ]T, and the camera moton between tme t and tme t +s composed of a translaton T and rotaton R (3 3 matrx). The projecton of the feature at tme t s: xt y t = A Xt Y t z t, () Z t and the projecton at tme (t +)s: xt+ = A Xt+ = A R xt+ y t+ z t+ y t+ z t+ Y t+ Z t+ Xt Y t Z t Therefore, the feature moton n the mage s: = A R A xt y t + T z t = U xt y t z t + T. () + V, (3) where U = A R A sa3 3 matrx and V = A T sa3- vector. Let [c t,rt ]=[xt /zt,yt /zt ] denote the actual column and row locaton of feature n mage coordnates at tme t. We then have the predcted feature locatons at tme t +as: ĉ t+ = u 00x t + u 0y t + u 0z t + v 0 u 0 x t + u y t + u z t + v, (4) ˆr t+ = u 0x t + u y t + u z t + v u 0 x t + u y t + u z t + v, (5) where u j and v are elements of U and V, respectvely. There are two ways to optmze the camera motons n the above equatons. One s to reduce the two equatons nto one by elmnatng z t. We would then mnmze the summed devaton from the equaton specfyng a nonlnear relaton between [c t,rt ] and [ĉt+, ˆr t+ ]. Though ths method s concse and smple, t poses a problem n the context of least-squares mnmzaton n that the objectve functon does not have a physcal meanng. The other approach to refne the moton estmate s to augment the parameters wth depth estmates for each of the features. There are two advantages to ths approach. Frst, the objectve functon becomes the dstance between the predcted and observed feature locatons, whch s a meanngful measure for optmzaton. In addton, n the context of mappng descent mages, we have a good ntal estmate of the depth value from the spacecraft altmeter. Incorporatng ths nformaton wll thus mprove the optmzaton n general. Let us say that the depth value of feature at tme t s d t and the camera s pontng along the z-axs; the homogeneous coordnates of the feature are [x t,yt,zt ]T = d t [ct,rt, ]t. Therefore, the overall objectve functon we are mnmzng s: N = ( (c t+ ĉ t+ ) ( + r t+ ˆr t+ ) ), (6) where N s the number of features and ĉ t+ and ˆr t+ are nonlnear functons of the camera moton and depth value d t gven by Eqs. 4 and 5. We perform nonlnear mnmzaton usng the Levenberg Marquardt algorthm wth the estmated poston as the startng pont. Robustness s mproved through the use of robust statstcs n the optmzaton. The result of the optmzaton s a refned estmate of the rotaton R and translaton T between the camera postons. In the optmzaton, we represent the rotaton usng a quaternon. In order to resolve between translatons and rotatons, whch appear smlar, a penalty term s added to the objectve functon Eq. 6 that prefers motons close to the ntal moton estmate. Ths constrans the moton not to devate far from the orentaton estmated by navgaton sensors whle allowng for some devaton n order to ft the observed data. An addtonal penalty term s added that forces the quaternon to have unt length and, thus, correspond to a vald rotaton matrx. Equaton 6 specfes the objectve functon for two adjacent mages. A long sequence of descendng mages requres a common scale reference n order to buld consstent multresoluton depth maps. The key to achevng ths s to track features over more than two mages. From Eq. 3 the depth value of feature at tme t +can be represented as d t+ ct+ r t+ = Ud t ct r t + V. (7) Thus, the overall objectve s to mnmze the sum of Eq. 6 for all adjacent pars whle mantanng the consstent scale reference by mposng the constrant n Eq. 7 for all features tracked over more than two frames. 3 Depth map recovery The second step of our method generates depth maps by performng correlatons between mage pars. In order to compute the mage correlaton effcently, we could rectfy the mages n a manner smlar to bnocular stereo. Unfortunately, we cannot smply rectfy the mages along scanlnes because the eppolar lnes ntersect near the center of the mages. If we resample the mages along eppolar lnes, we wll oversample near the mage center and undersample near the mage boundares. Alternatve rectfcaton methods have recently been proposed that mprove handlng of these ssues [9,0]. However, these methods enlarge the mages and resample unevenly. Another alternatve s to not resample the mages at all. Matches can be found along the eppolar lnes even f they are not horzontal. Ths method, however, requres consderably more computaton tme. In order to avod these problems and perform the correlaton effcently, we adopt a slcng algorthm. The man dea s to use a set of vrtual planar surfaces slcng through the terran as shown n Fg. 3. A smlar concept was used by Collns [] to perform matchng between features extracted from the mages. See also []. The vrtual planar surfaces are smlar n concept to horopter surfaces [] n stereo. For every planar surface k, f a terran surface patch les on the planar surface, then there exsts a projectve warpng P k between the two mages for ths patch. If we desgnate the frst mage I (x, y) and the second mage I (x, y), then for every vrtual planar surface, we can

4 Yaln Xong et al.: Computng depth maps from descent mages Fg. 3. The terran s slced wth vrtual parallel planes compute the sum of squared dfferences (SSD) as: C k (x, y) = x+w I I y+w m=x W n=y W Terran ( I (m, n) I k (m, n) ), (8) where W +s the sze of the correlaton wndow and I k (x, y) s a warped verson of I (x, y): ), I k (x, y) =I ( p00 x + p 0 y + p 0 p 0 x + p y + p, p 0x + p y + p p 0 x + p y + p (9) where p j are elements of the 3 3 matrx P k. Due to the large resoluton dfference, an ant-alasng resamplng [5] or a unform downsamplng of I (x, y) s appled before the mage warpng. In practce, f the camera headng drectons are almost perpendcular to the ground, a unform downsamplng before warpng s suffcent. Otherwse, a space-varant downsamplng should be used to equalze the mage resolutons. The estmated depth value at each pxel s the depth of the plane z k whose correspondng SSD mage pxel C k (x, y) s the smallest: z(x, y) =z k, (0) where C k (x, y) C j (x, y),j =,...,M, () and M s the number of planar surfaces. To further refne the depth values, the underlyng SSD curve can be nterpolated by a quadratc curve and the subpxel depth value computed [5] as: δz(c k+ (x, y) C k (x, y)) z(x, y) =z k + (C k+ (x, y)+c k (x, y) C k (x, y)), () where δz s the depth ncrement between adjacent planar surfaces. In order to mprove the localzaton of ths operaton, we compute the SSD between the wndows wth a Gaussan modulaton functon so that the pxels closer to the center of the wndow have more weght than the pxels at the edge of the wndow. The projectve warpng matrx P k s derved from the parameters of the camera moton and the planar surfaces. For an arbtrary pont X n some reference frame, ts projecton s expressed as x = M( X C), where C s the poston of the camera nodal pont and M s the projecton matrx. Note that C and M encapsulate the camera moton between the mages, snce they are represented n a common reference frame. Let C and M represent the hgher camera, C and M represent the lower camera n Fg. 3. N T X + zk =0represents the set of planar surfaces. For any pxel n mage (.e., the lower camera), ts locaton must le on a 3D ray: X = s M c r + C, (3) where c and r are, respectvely, the column and row locaton of the pxel and s s a postve scale factor. If the pxel s from a pont on the planar surface, then the followng constrant must be satsfed: s N T M Therefore, the scale factor s must be c r + N T C + z k =0. (4) N T C + z k s = N T M [c,r, ]. (5) T We can then reproject the pont onto the frst mage usng Eqs. 3 and 5: x y = M ( X C )= P k c r, (6) z where P k sa3 3 matrx specfyng the projectve warpng: P k = M ( C C ) N T M ( N T C +z k ) M M. (7) Note that the depth recovery s numercally unstable n the vcnty of the eppoles, located near the center of the mage. Pxels near the eppoles usually have a small amount of parallax, even wth large camera motons. The SSD curves n these areas are very flat, and, thus, accurate depth recovery s dffcult. These regons can be easly fltered, f desred, by mposng a mnmum curvature threshold at the mnma of the SSD curves. 4 Experments Fgure 4a c shows a synthetc set of nested descent mages ( pxels). For ths set of mages, the terran model s composed of a slowly varyng terran surface overlad wth rocks dstrbuted accordng to a statstcal model. The heght of the camera decreases from 5 m above the ground to 6 m above the ground. The feld of vew of the camera s 70. Fgures 4d,e show a vsualzaton of the depth maps, wth the mage draped over the terran. The maps have root-meansquare errors of 4.6 cm and 9.7 cm, respectvely. Note that the In the notaton of the prevous secton, M = A, C = 0, M = AR, and C = R T. The change of notaton s prmarly for convenence.

5 Yaln Xong et al.: Computng depth maps from descent mages a b c d e Fg. 4a e. Synthetc descent mage sequence. a Image at 6 m elevaton. b Image at m elevaton. c Image at 5 m elevaton. d Rendered terran map at 6 m elevaton. e Rendered terran map at m elevaton a b c d e f g h Fg. 5a h. Descent sequence captured wth a helcopter. a Elevaton: 085 m. b Elevaton: 590 m. c Elevaton: 38 m. d Elevaton: 8 m. e Elevaton: 55 m. f Elevaton: 3 m. g Elevaton: 5 m. h Elevaton: 8 m areas close to the focus of expanson (at the center of the mage) have larger error than the rest of the mage, owng to the geometrcal nstablty at the focus of expanson. In both mage pars, the general downward slope of the terran from back to front and left to rght can be observed. In addton, ndvdual rocks can be dstngushed, partcularly n the lower-elevaton mage par. These technques have been tested extensvely on smlar synthetc mages wth smlar results. For these experments, we generated our ntal estmates of the camera moton by perturbng the actual camera values by a random nose of magntude. Ths level of accuracy n the orentaton can be acheved by the onboard nertal navgaton system durng an actual landng. The overall qualty of the recovered depth maps appears adequate for navgaton n the vcnty of the landng and long-range plannng of goals far from the landng ste. Our technques were also tested usng a set of descent mages collected n the desert area near Slver Lake, CA usng a helcopter. Fgure 5 shows eght frames from ths sequence. The ntal camera motons were estmated usng control ponts

6 Yaln Xong et al.: Computng depth maps from descent mages a b c d e f g Fg. 6a g. Rendered terran maps. a Elevaton: 590 m. b Elevaton: 38 m. c Elevaton: 8 m. d Elevaton: 55 m. e Elevaton: 3 m. f Elevaton: 5 m. g Elevaton: 8 m on the ground. Several of the mages contan sgnfcant lateral motons due to the dffculty n mantanng the x-y poston of the helcopter durng the data collecton. Fgure 6 shows the mages draped over the vsualzed terran, and Fg. 7 shows the same data wthout texture mappng. Snce these are real mages captured usng a movng helcopter, the focus of expanson for each mage par s not at the center of the mage (although t s reasonably close n Fgs. 6b and e). In Fgs. 6f and g, the focus of expanson can be seen above the center of the mage, whle t s near the bottom-rght corner n Fgs. 6c and d. In Fg. 6a, the focus of expanson s off of the mage to the left. The nstablty can be seen n these locatons where the rendered map becomes wavy or choppy. As the dstance from the focus of expanson ncreases, the terran elevatons become more accurate. In Fg. 6c, the lower alttude mage dd not entrely overlap the hgher alttude mage, resultng n the lack of elevaton data n the lower-left corner of the result for that mage par. For the mages n ths data set, the terran slopes downward from left to rght, whch can be observed n the rendered maps. Some of the nterestng terran features nclude the channels n Fgs. 6c e and the bushes vsble n Fg. 6g. Note that the areas n whch the helcopter shadow s present yeld good results, despte the movement of the shadow. Ths can be attrbuted to the robust methods that we use for both moton estmaton and template matchng. Overall, ths data set ndcates that we can robustly compute maps that are useful for navgaton over both small and large scales usng real mages, albet under somewhat dfferent condtons than would be encountered by an actual Mars lander. Whle no descent mages are currently avalable from other planets, the three fnal Ranger mssons to the moon (Ranger 7 n 964, Ranger 8 n 965, and Ranger 9 n 965) transmtted mages on ther descent to the surface. In fact, the msson of these spacecraft was to return mages whle crashng nto the moon at flght velocty. Unfortunately, these mages are

7 Yaln Xong et al.: Computng depth maps from descent mages a b c d e f g Fg. 7a g. Rendered terran maps wthout texture mappng. a Elevaton: 590 m. b Elevaton: 38 m. c Elevaton: 8 m. d Elevaton: 55 m. e Elevaton: 3 m. f Elevaton: 5 m. g Elevaton: 8 m dffcult to work wth, snce the camera was uncalbrated and the mages were transmtted n analog form. Fgure 8 shows mages from Ranger 7 and Ranger 9 and rendered terran maps that show qualtatve results wth respect to the shape of the terran. Hgh-qualty quanttatve results are not possble wth these data. Nevertheless, we are able to extract nterestng data wth respect to the slope of the terran and certan depressons caused by mpact craters. For the Ranger 7 mage, the focus of expanson occurs at the upper-left corner of the mage. For the Ranger 9 mage, the focus of expanson occurs just above the large crater that s vsble. 5 Summary method conssts of two prmary steps: moton estmaton and depth recovery. Moton estmaton s performed by matchng features and mnmzng a least-squares objectve functon usng nonlnear methods. The depth map s then recovered usng a novel technque where the terran s slced by vrtual planes, smlar to horopter surfaces n stereo. Each plane can be thought of as a vertcal dsplacement. The plane yeldng the lowest SSD s selected as the depth for each pxel, and subpxel estmaton technques are used to mprove the estmate. We have performed experments wth ths method on synthetc and real mage sequences. The experments have resulted n maps that can be used for navgaton and plannng at a scale roughly proportonal to the dstance from the landng ste. We have presented technques for extractng depth maps from a sequence of descent mages, such as those that would be acqured by a lander descendng to a planetary surface. The

8 Yaln Xong et al.: Computng depth maps from descent mages a b c d Fg. 8a d. Moon mages from Ranger mssons. a Moon mage from Ranger 7. b Rendered terran map. c Moon mage from Ranger 9. d Rendered terran map. Acknowledgements. The research descrbed n ths paper was carred out n part at the Jet Propulson Laboratory, Calforna Insttute of Technology, under a contract wth the Natonal Aeronautcs and Space Admnstraton. An earler verson of ths work appeared n the 00 IEEE Computer Socety Conference on Computer Vson and Pattern Recognton [6]. References. Burt PJ, Wxson L, Salgan G (995) Electroncally drected focal stereo. In: Proceedngs of the nternatonal conference on computer vson, pp Collns RT (996) A space-sweep approach to true mult-mage matchng. In: Proceedngs of the IEEE conference on computer Vson and pattern recognton, pp Förstner W (994) A framework for low-level feature extracton. In: Proceedngs of the European conference on computer vson, pp Hanna KJ (99) Drect mult-resoluton estmaton of egomoton and structure for moton. In: Proceedngs of the IEEE workshop on vsual moton, pp Heckbert P (986) Survey of texture mappng. IEEE Computr Graph Appl 6(): Heeger DJ, Jepson AD (99) Subspace methods for recoverng rgd moton: I. Algorthm and mplementaton. Int J Comput Vs 7(): Longuet-Hggns HC (98) A computer algorthm for reconstructng a scene from two projectons. Nature 93: Olenss J, Genc Y (999) Fast algorthms for projectve multframe structure from moton. In: Proceedngs of the nternatonal conference on computer vson, : Pollefeys M, Koch R, Van Gool L (999) A smple and effcent rectfcaton method for general moton. In: Proceedngs of the nternatonal conference on computer vson, : Roy S, Meuner J, Cox IJ (997) Cylndrcal rectfcaton to mnmze eppolar dstorton. In: Proceedngs of the IEEE conference on computer vson and pattern recognton, pp Soatta S, Perona P (998) Reducng structure from moton : a general framework for dynamc vson, part : Modelng. IEEE Trans Pattern Anal Mach Intell 0(9): Szelsk R, Golland P (999) Stereo matchng wth transparency and mattng. Int J Comput Vs 3(): Szelsk R, Kang SB (994) Recoverng 3d shape and moton from mage streams usng non-lnear least squares. J Vs Commun Image Represent 5(): Tomas C, Kanade T (99) Shape and moton from mage streams under orthography: a factorzaton method. Int J Comput Vs 9(): XongY. Matthes LH (997) Error analyss for a real-tme stereo system. In: Proceedngs of the IEEE conference on computer vson and pattern recognton, pp Xong Y, Olson CF, Matthes LH (00) Computng depth maps from descent magery. In: Proceedngs of the IEEE conference on computer vson and pattern recognton, :39 397

9 Yaln Xong et al.: Computng depth maps from descent mages Yaln Xong s Drector of Engneerng n RAPID dvson of KLA- Tencor, specalzng n mage processng and computer vson algorthms for semconductor nspecton equpments. Pror to jonng KLA-Tencor, he was a senor staff n Jet Propulson Lab, Caltech from 998 to 000, and senor engneer n Apple Computer from 996 to 998. Dr. Yaln Xong got Ph.D. from the Robotcs Insttute of Carnege Mellon Unversty, and B.S. from the Unversty of Scence and Technology of Chna. Clark F. Olson receved the B. S. degree n computer engneerng n 989 and the M.S. degree n electrcal engneerng n 990, both from the Unversty of Washngton, Seattle. He receved the Ph. D. degree n computer scence n 994 from the Unversty of Calforna, Berkeley. After spendng two years dong research at Cornell Unversty, he moved to the Jet Propulson Laboratory, where he spent fve years workng on computer vson technques for Mars rovers and other applcatons. Dr. Olson joned the faculty at the Unversty of Washngton, Bothell n 00. Hs research nterestes nclude computer vson and moble robotcs. He teaches classes on mathematcal prncples of computng, database systems, and computer vson. He contnues to work wth NASA/JPL on computer vson technques for Mars exploraton. Larry H. Matthes PhD, computer scence, Carnege Mellon Unversty, 989; Supervsor, Machne Vson Group, Jet Propulson Laboratory (JPL). Dr. Matthes has years experence n developng percepton systems for autonomous navgaton of robotc ground and ar vehcles. He poneered the development of real-tme stereo vson algorthms for range magng and accurate vsual odometry n the 980 s and early 990 s. These algorthms wll be used for obstacle detecton onboard the Mars Exploraton Rovers (MER). The GESTALT system for obstacle avodance for the MER rovers was developed n hs group; ths system s also currently the baselne for onboard obstacle detecton for the 009 Mars Scence Laboratory (MSL) msson. Hs stereo vson-based range magng algorthms were used for ground operatons by the Mars Pathfnder msson n 997 to map terran wth stereo magery from the lander for plannng daly operatons for the Sojourner rover. He ntated the development at JPL of computer vson te s for autonomous safe landng and landng hazard avodance for mssons to Mars, asterods, and comets. Hs group developed the Descent Image Moton Estmaton System (DIMES) that wll be used to estmate horzontal velocty of the MER landers durng termnal descent. Algorthms developed n hs group for onboard crater recognton have been selected as the backup approach to regonal hazard avodance for the MSL msson. He also conducts research on terran classfcaton wth a wde varety of sensors for off-road navgaton on Earth. He was awarded the NASA Exceptonal Achevement Medal n 00 for hs contrbutons to computer vson for space mssons. He s an Adjunct Assstant Professor of Computer Scence at the Unversty of Southern Calforna.