FULL-FRAME VIDEO STABILIZATION WITH A POLYLINE-FITTED CAMCORDER PATH

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1 FULL-FRAME VIDEO STABILIZATION WITH A POLYLINE-FITTED CAMCORDER PATH Jong-Shan Ln ( 林蓉珊 ) We-Tng Huang ( 黃惟婷 ) 2 Bng-Yu Chen ( 陳炳宇 ) 3 Mng Ouhyoung ( 歐陽明 ) Natonal Tawan Unversty E-mal: {marukowetng}@cmlab.cse.ntu.edu.tw 2 robn@ntu.edu.tw 3 mng@cse.ntu.edu.tw ABSTRACT Annoyng shaky moton s one of the sgnfcant roblems n home vdeos snce hand shake s an unavodable effect when caturng by usng a hand-held camcorder. Vdeo stablzaton s an mortant technque to solve ths roblem. However the stablzed vdeos resulted by current methods usually have decreased resoluton and are stll not so stable. In ths aer we roose a novel robust and ractcal method of vdeo stablzaton wth a olylne-ftted camcorder ath. Our method can roduce full-frame stablzed vdeos and not only has the hgh frequency shaky motoned but also the low frequency unexected movements are removed. To acheve ths we use a olylne to estmate a new stable camcorder moton ath and then we fll the dynamc and statc mssng areas caused by frame algnment from other frames to kee the same resoluton and qualty as the orgnal vdeo. Furthermore we smooth the dscontnuous regons by usng a three-dmensonal Posson-based method. After the above automatc oeratons a full-frame stablzed vdeo can be acheved.. INTRODUCTION As the use of dgtal camcorders grows to cature vdeos usng hand-held camcorders becomes more and more convenent than before. However snce most eole usually do not brng a trod wth ther camcorders unwanted vbraton n vdeo sequence s an unavodable effect due to the handshakes. To avod or remove the annoyng shaky moton s one of the sgnfcant roblems n home vdeos and vdeo stablzaton s an mortant technque to solve ths roblem. Many exsted vdeo stablzaton alcatons result a stablzed vdeo by smoothng the camcorder moton ath and then truncatng the mssng areas after algnng the vdeo frames along the smoothed moton ath. Hence the stablzed vdeos stll have many unexected movements snce only hgh frequency shaky motons are removed durng the smoothng stage. Moreover the vdeo qualtes of the stablzed vdeos are usually decreased due to the truncatng stage. In ths aer we roose a novel robust and ractcal method of full-frame vdeo stablzaton wth a olylne-ftted camcorder ath. To acheve ths we use a olylne to estmate a new stable camcorder moton. Hence the resulted vdeos are much stable and much close to the vdeos that the users want to cature. Once we obtan a new stable camcorder moton ath of the vdeo the vdeo frames are algned along the new moton ath to form a stablzed vdeo. Due to the frame algnment there are several mssng areas n the new stablzed vdeo. Unlke other trmmng aroaches we fll the dynamc and statc mssng areas resectvely by usng moton nantng and wared neghborng vdeo frames. Ths comleton method works well even f there are some movng objects located at the boundary of the vdeo frames whle keeng the same resoluton and qualty as the orgnal vdeo. However snce we use a olylne to ft the camcorder moton ath rather than usng a arametrc curve to smooth the moton ath the mssng areas are usually large and cannot be easly comleted by neghborng frames. To fll the mssng areas usng the xels on the frames far from the current frame may cause the dscontnuty at the boundares of the flled areas snce the ntensty of each vdeo frame s usually not necessarly the same. Hence we smooth the dscontnuty boundares by usng a three-dmensonal Posson-based method whch takes both of the satal and temoral consstency nto consderaton and can result seamless sttchng satally and temorally. After stablzng the vdeos the blurry vdeo frames also caused by the handshakes become much notceable. Hence we detect the blurry frames and transfer the xels from neghborng sharer frames. Therefore our method can roduce full-frame stablzed vdeos and not only has the hgh frequency shaky motoned but also the low frequency unexected movements are removed. The stablzed vdeos are stable comfortable and much more close to the vdeos whch the users

2 really want to cature f they brng a trod wth them when caturng. 2. RELATED WORK Vdeo stablzaton s an mortant research toc n multmeda mage rocessng comuter vson and comuter grahcs. Buehler et al. roosed an magebased renderng (IBR) method to stablze vdeos [4]. Recently mage rocessng methods are wdely used for vdeo stablzaton. For estmatng the camcorder moton ath Ltvn et al. estmated a new camcorder moton ath by alterng camera arameter [9] and Matsushta et al. smoothed the camcorder moton ath to reduce the hgh frequency shaky motons []. However although the hgh frequency shaky motons can be easly reduced the stablzed vdeos stll have low frequency unexected movements. When fllng u the mssng mage areas there are some mage nantng aroaches develoed for recoverng the mssng holes n the mage [ 5 8]. Although these aroaches can comlete the mssng regons wth correct structure but there wll be obvous dscontnuty f we recover each vdeo frame resectvely. Ltvn et al. used mosac method to fll u the mssng areas n the stablzed vdeo [9] however they dd not consder the movng objects may aear at the boundary of the vdeo. Wexler et al. and Shrator et al. flled u the mssng holes by samlng the satotemoral volume atches from other orton of the vdeo volume [5 6]. The former aroach used the most smlar atch n color sace for comletng the mssng holes and the later one used the atch wth smlar moton vector. The drawback of these methods s that they need large comutng tme for searchng a roer atch. Ja et al. and Patwardhan et al. segmented the vdeo nto two layers and recovered them ndvdually [7 3]. These methods focused on long and erodc observed tme of the movng objects but ths s not guaranteed n common home vdeos. called moton ath estmaton (Sec. 4). In ths rocess the camcorder moton ath of the orgnal vdeo s estmated and changed to be a stablzed one. There are three stes contaned n ths rocess. In the frst ste (Sec. 4.) we fnd out the transformaton between the consecutve frames and combne all of the transformatons to obtan the global camcorder moton ath of the orgnal vdeo. In the second ste (Sec. 4.2) the estmated global camcorder moton ath s aroxmated by a olylne snce the camcorder moton ath of the vdeo catured by usng a trod s lke a olylne. After the stablzed camcorder moton ath s acheved the vdeo comleton rocess s aled (Sec. 5). Because the oston of each frame s changed accordng to the frame algnment along the new moton ath there are some mssng areas wthn each algned frame. The frst ste n the vdeo comleton s to detect f there exsts movng objects and where they are (Sec. 5.). In the second ste we searate the movng objects as the dynamc foreground regons from the statc background regons and comlete the mssng areas of them by dfferent methods (Sec. 5.2 and 5.3). To fll the mssng areas usng the xels on the frames far from the current frame may cause the dscontnuty at the boundares of the flled areas snce the ntensty of each vdeo frame s usually not necessarly the same. In order to make a seamless sttchng we aly a threedmensonal Posson-based smoothng method on the dscontnuous regons (Sec. 5.4). 3. OVERVIEW Inut orgnal vdeo sequence Outut stablzed vdeo sequence Moton Path Estmaton Global Path Estmaton Poly-lne Fttng Vdeo Deblurrng Vdeo Comleton Movng Object Detecton Dynamc Regon Comleton Fg. : System framework. Posson-based Smoothng Statc Regon Comleton Fg. shows the system framework of our algorthm. The nut of our system s a vdeo sequence catured by a hand-held camcorder wthout usng a trod. Hence the vdeo sequence has much annoyng shaky motons due to the handshakes. The frst rocess of our system s Fg. 2: To row: Three frames of the orgnal vdeo. There are annoyng shaky motons n the frames. Mddle row: Stablzed frames. Black areas show the mssng areas of the frames. Bottom row: Comleted frames. Ths s the result of our method; the shaky motons of the vdeo are removed. The last rocess s vdeo deblurrng (Sec. 6). Because the moton blur of each frame may not be matched n the stablzed camcorder moton ath the blurry frames become much notceable n the new stablzed vdeo. Instead of fndng the accurate ont sread functon for mage deblurrng we choose a vdeo

3 deblurrng method by transferrng the xel values from neghborng sharer frames to the blurry frames. After the above automatc rocesses the outut wll be a stablzed vdeo wth stable camcorder moton ath whle keeng the same resoluton and qualty as the orgnal one. Fg. 2 shows three frames of an nut vdeo and ther stablzed results before and after the vdeo comleton and deblurrng rocesses. 4. MOTION PATH ESTIMATION In order to generate stablzed vdeos we frst estmate the camcorder moton ath of the orgnal vdeo (Sec. 4.). Then the orgnal camcorder moton ath s stablzed by usng a olylne-based moton ath (Sec. 4.2) so that the undesrable moton caused by hand shake can be removed. 4.. Global Path Estmaton To estmate the global camcorder moton ath we frst extract the feature onts of each frame by SIFT (Scale Invarant Feature Transform) [0] whch s nvarant to scalng and rotaton of the mage. The feature onts on every consecutve frame are matched f the dstances between the feature descrtons are small enough and RANSAC (RANdom SAmle Consensus) [6] s used to select the nlers of the matched feature ars. For the accuracy an over-constraned system s aled to fnd out the least square soluton between these matched feature ars and derve the affne transformaton between the two consecutve frames. The affne transformaton s reresented by a 3 3 affne model whch contans sx arameters. That means f we fnd out the transformaton matrx T between frames and + the corresondng xel on the frame and xel + on the frame + have the followng relatonsh: + T. Once the transformaton matrces between the consecutve frames are obtaned all of the transformatons can be combned to derve a global transformaton chan. and M = HK + v H = K+ =Φ K + w Φ= where Φ s the state transton model whch s aled to the revous state K to aroxmate the next state K + H s the observaton model whch mas the true state sace M nto the observed sace K v ~ N (0 R) s the observaton nose whch s assumed to be a zero mean Gaussan whte nose wth covarance R and w~ N(0 Q) s the rocess nose whch s assumed to be drawn from a zero mean multvarate normal dstrbuton wth covarance Q. The camcorder moton ath smoothed by the Kalman flter s shown as the green curves n Fg. 3. xel 50 = horzontal camera moton frame vertcal camera moton orgnal camera ath fltered by Kalman flter olylne 4.2. Moton Path Fttng To obtan a stablzed camcorder moton ath wthout not only the hgh frequency shaky motons but also the low frequency unexected movements we use a olylne to ft the estmated global camcorder moton ath. We frst searate the camcorder moton ath estmated from Sec. 4. to be horzontal and vertcal ones M = [ xy ] and oerate them resectvely. Then Kalman flter s emloyed to estmate a smooth camcorder moton ath K of M [2] whch s reresented n two-dmensonal sace as xel orgnal camera ath fltered by Kalman flter olylne frame Fg. 3: The orgnal camcorder moton ath (red curve) and the estmated camcorder moton ath after alyng Kalman flter (green curve) and fttng by a olylne (blue straght lne) for horzontal (Uer) and vertcal (Lower) moton aths.

4 After alyng the Kalman flter we can obtan the smoothed camcorder moton ath (Kalman ath). Then we use a olylne to ft the Kalman ath. We frst assume there s only one straght lne connected the camcorder oston of the frst frame and that of the last frame on the Kalman ath. Then we calculate the dfference between the camcorder oston n the orgnal moton ath of each frame and the temorary moton ath (the straght lne) and fnd the maxmal dfference. If the maxmal dfference s larger than the a threshold the straght lne s broken by connectng the camcorder oston of ths frame on the Kalman ath and the endonts of the straght lne and hence the temorary camcorder moton ath (the straght lne) becomes a olylne wth two straght lne segments. Ths ste s erformed teratvely untl the temorary camcorder moton ath can reserve all mortant regons n the vdeo. The fnal camcorder moton ath s shown as the blue olylne n Fg. 3. Once the camcorder moton ath s ftted by a olylne the vdeo frames are algned along the olylne ftted camcorder moton ath. If the global transton matrx from the frst frame to the -th frame s denoted by M then the -th frame s algned to 0 j j = M T where means the xels on the -th frame and T reresented affne transformaton matrx between j -th frame and j + -th frame. Hence we can obtan a stablzed vdeo after the olylne fttng and frame algnment. 5. VIDEO COMPLETION After algnng the vdeo frames along the stablzed camcorder moton ath there are several mssng areas n the new stablzed vdeo. Tradtonally ths roblem could be solved by cuttng out the mssng areas and scalng the stablzed vdeo to ts orgnal sze but t may result a stablzed vdeo wth worse resoluton. Hence to make the resoluton of the stablzed vdeo as good as that of the orgnal one the mssng areas are flled from other frames. To comlete the vdeo we frst detect the movng objects to segment the vdeo to a statc background regon and some dynamc movng object regons (Sec. 5.). Then we comlete the mssng areas by fllng dynamc regons (Sec. 5.2) and statc regons (Sec. 5.3) resectvely. Snce the camcorder moton ath s ftted by a olylne the mssng areas may be large and need to be flled by the xels on the frames far from the current frame so we rovde a three-dmensonal Posson-based smoothng method to smooth the dscontnuty sttched areas (Sec. 5.4). 5.. Movng Object Detecton In order to detect movng objects we frst algn every ar of adjacent frames by usng the affne transformaton obtaned n Sec. 4.. Then we evaluate the otcal flow of them by usng an effcent and less nosy otcal flow aroach [2 3] to obtan the moton vector of each xel. The moton vector of xel can be descrbed as F( ) whch reresents the moton flow at xel from frame to frame + and the length of the moton vector shows the moton value. Fg. 4: Left: The frame after changng the oston accordng to the stablzed camcorder moton ath. Rght: The mask of detected movng objects (whte regons). The moton values n the movng object regons are consdered to be relatvely larger than those n the statc background regon. Hence we can get a smle mask to show the regons wth large moton values by a smle threshold as shown n Fg. 4. The dynamc regons are obtaned by evaluatng the dlaton of the mask whch can hel to guarantee the boundary of the movng objects s nvolved n the dynamc regons. If the mssng area falls n the regons where the neghborng xels have been asked as the dynamc regon ths area s treated as the dynamc regon and moton nantng s used to comlete the area otherwse we recover the area by mosacng Dynamc Regon Comleton For the dynamc mssng regons nstead of fllng n the color values from other frames drectly we want to fll them u wth correct moton vectors. Once we derve the moton vectors of each xel n the mssng areas we can get the xel color from the next frame accordng to the moton vectors. The local moton vectors n the known mage areas are roagated to the dynamc mssng areas as descrbed n []. Frst local moton vectors are estmated by comutng the otcal flow between the stablzed frames [2 3]. The roagaton starts at the xel on the boundary of the dynamc mssng areas ts moton vector s calculated as a weghted average of the moton vectors of ts neghborng xels. The rocess wll contnue untl the dynamc mssng areas are flled wth moton vectors comletely. If s a xel n the mssng area t wll be flled accordng to ts moton vector whch s determned by

5 w here w ( q) moton F( ) = q N q N wq ( ) F w ( q) determnes the contrbuton of the vector of xel q N denotes the eght F reresents the neghborng xels of and ( ) moton vector at xel from fr ame to frame +. Suose the neghborng xel q N already has a moton vector accordng to ts moton vector we can estmate ts oston on the next frame as q +. By usng the geometrc relatonsh between the xels and q the oston of the xel + n the frame + can also be determned as llustrated n Fg. 5. Snce the xels n the same object have smlar color values and move n the same drecton f the dfference between the color values of the xels q + and + s small they wll lkely belong to the same object and the weght of the moton vector of xel q s set to be large as wraed to the current frame accordng to the affne transformaton obtaned n Sec. 4.. For the xel n the statc mssng area at frame f there exsts ts corresondng xel at the wared neghborng frame ' we drectly coy the xel to the mssng xel by = T ' ( ') where T ' reresents the transformaton from frame ' to frame. Fg. 7 llustrates the rocess and Fg. 8 shows the statc regon comleton result. w ( + q) = ( ClrD( q ) + ε ) + + where ε s a small value for avodng the dvson by 2 zero and ClrD( + q+ ) s the l -norm color dfference n RGB color sace of the xels q + and +. Ths weght t erm guarantees that the contrbuton of the moton vector n dfferent object s s smal l. Fg. 6 shows the result. q + Fg. 6: Uer-Left: The frame after changng the oston accordng to the stablzed camcorder moton ath. There s a mssng area at the left sde and a movng object across the mssng area. Lower-Left: The result of dynamc regon comleton. Rght Column: The close u vew of the yellow square of the Left Column. mssng area + q + frame - frame frame + frame 2 q 3 q unknown moton frame q q Fg. 7: s a xel n the mssng area at current frame and + s ts corresondng xel n the next frame +. The xel value of + s drectly coed to for recoverng the mssng xel. Fg. 5: Suose the neghborng xel q already has a moton vector accordng to ts moton vector we can estmate ts oston on the next frame as q +. By usng the geometrc relatonsh between the xels and q the oston of the xel + n the frame + can also be determned Statc Regon Comleton After comletng the dynamc regons we then recover the statc ones by ts neghborng frames whch are Fg. 8: Left: The frame after changng the oston accordng to the stablzed camcorder moton ath. There s a mssng area at the rght sde and uer sde. Rght: The result of statc regon comleton. Snce the mssng area s large there s a dscontnuty boundary between the recovered xels and the orgnal frame.

6 To fnd the corresondng xel of we begn the search from the nearest neghborng frame and roagate the search out. For examle f s the current frame we want to recover we search the frames and + frst f there are mssng areas stll have not been recovered by the two frames the followng two frames 2 and + 2 are used to recover the mssng areas. We kee the search untl all the mssng xels n the statc mssng areas are comleted. Fnally f there are stll some mssng areas we cannot recover we use a smle mage nantng aroach to comlete them. values of the mssng areas by aly the Posson equaton agan. For the mssng areas now we consder not only the satal neghborng xels but also temoral neghborng xels. Hence the Posson equaton s the same but N ncludes all neghborng xels of xel n the vdeo volume. Fg. 9 shows the result Posson-Based Smoothng Although the mssng areas caused by the stablzed camcorder moton ath are comleted there may be a dscontnuous boundary between the recovered xels and the orgnal frame snce the mssng areas may be large and needed to be flled from the frame far from the current one. Ths roblem may be solved by smly alyng some smoothng aroaches for the boundary areas; however these smly smoothng oeratons can only solve the satal dscontnuty roblem. When we lay the satally smoothed vdeo t stll has temoral dscontnuty roblem. In order to kee the satal and temoral contnuty we rovde a three-dmensonal Posson-based smoothng method. Posson-based smoothng aroach s often used n mage edtng [4] and we extend ths aroach for vdeo edtng. To solve the dscontnuty roblem before fllng n a xel from other frames the Posson equaton s aled to obtan a smoothed xel by consderng ts neghborng xels n the same frame and neghborng frames. We frst aly the Posson equaton n the satal doman whch s wrtten as: For all Ω N f f = f + * q q q q N Ω q N Ω q N where Ω denotes the mssng area s a xel n the mssng area Ω N denotes the neghborng xels of xel N s the number of neghborng xels N f and f q are the correct xel values of xels and q whch are what we want to derve vq determnes the dvergen ce of xels and q Ω s the regon surroundng the mssng area Ω n the known mage * areas and f q denotes the known color value of xel q n Ω. The Posson equaton can kee the correct structure n the mssng area and acheve a seamless sttchng between the recoverng areas and known mage areas. In order to acheve temoral coherence after recoverng the mssng areas of each frame we correct the xel v Fg. 9: Uer-Left: The frame after vdeo comleton. Snce the mssng area s large there s a dscontnuous boundary between the recovered xels and the orgnal frame. Lower-Left: The result of vdeo comleton wth Posson-based smoothng. Rght Column: The close u vew of the yellow square of the Left Column. 6. VIDEO DEBLURRING After vdeo stablzaton the blurry frames whch look smooth n the orgnal vdeo become notceable. Our vdeo deblurrng method fundamentally based on [] but we searate the movng objects from statc background frst and deal wth them resectvely as the vdeo comleton rocess. Snce the blur of the statc background s much more notceable than that of the movng objects n the followng exlanaton we only focus on the statc background deblurrng. The man dea of ths method s to coy the xels of neghborng sharer frames to the blurry frames. We frst evaluate the "relatve blurrness" of each frame by calculatng the gradent of t. Generally the gradent of blurry mage s smaller than that of sharer one at the same regons. Wth ths assumton the blurrness of frame s defned as: 2 2 B = ( gx( ) + gy( ) ) where s the xel of the frame and g x and g y are the gradents of x and y drectons resectvely. We can derve the relatve blurrness between the current frame and ts neghbor ng frames by comarng ther blurrnes s B. If the blurrness B of current frame s smaller than the blurrness B ' of ts neghborng frames then the frames are treated to be sharer than the frame and we can use the frames

7 to recover the current blurry frame by transferrng the corresondng xe ls from these sharer frames to the blurry frame by + w ( ) N T = + w N where and are th e same xel n the frame after and before the deblurrng oeraton N denotes the neghborng frames of current frame T reresents the transformat on from the neghborng frame N to frame and w s a weghtng factor between and whch s defned as: Fg. 0 shows the result of ths deblurrng method. 0 f / B B < w =. B / B otherwse bottom row of Fg. 2 shows our result and the stablzed camcorder moton ath s just lke to cature the scene by usng a trod. 8. CONCLUSION AND FUTURE WORK A full-frame vdeo stablzaton aroach s roosed n ths aer to obtan a stablzed vdeo. Snce we use a olylne to ft the orgnal camcorder moton ath the stablzed moton ath s much more stable than other smoothness aroaches. Hence n the stablzed vdeo not only the hgh frequency shaky motons but also the low frequency unexected movements are removed. Although usng a olylne to estmate the camcorder moton ath may cause large mssng areas t s solved by alyng a three-dmensonal Posson-based smoothng method. To fll the mssng areas from other frames and deal wth blurry frames we searate the movng objects from the statc background and deal wth them resectvely n comleton and deblurrng rocesses. ACKNOWLEDGEMENT Ths aer was artally suorted by the Natonal Scence Councl of Tawan under NSC E and also by the Excellent Research Projects of Natonal Tawan Unversty under 95R0062-AE REFERENCES [] M. Bertalmo G. Saro V. Caselles and C. Ballester Image Inantng Proc. ACM SIGGRAPH Fg. 0: Uer-Left : A blurry frame. Lower-Left:The result of vdeo deblurrng. Rght Colu mn: The close u vew of the yellow square of the Left Column. 7. RESULT All of the vdeos used n ths aer was catured by usng a hand-held vdeo camera wt hout usng a trod and the resoluton of the vdeos are all The resoluton of all stablzed vdeos s the same as the nut vdeos. Fg. 2 Fg. and Fg. 2 show our results. In Fg. 2 the user wants to use the hand-held camcorder to cature a anorama vew. Wthout a trod the catured vdeo s shaky due to the handshakes. In Fg. the user wants to use the handheld camcorder to cature a man walkng wth hs chld. Wthout a trod the catured vdeo s shaky due to the handshakes. The bottom rows of Fg. shows our result whch s stablzed as catured by usng a trod. In Fg. 2 the user wants to use the hand-held camcorder to cature a man layng wth hs dog but due to the vew angle lmtaton the user ans the camcorder a lttle bt to cature the whole scene. The [2] M. J. Black and P. Anandan A Framework for the Robust Estmaton of Otcal Flow Proc. IEEE ICCV [3] M. J. Black and P. Anandan The Robust Estmaton of Multle Motons: Parametrc and Pecewse-Smooth Flow Felds CVIU Vol. 63 No [4] C. Buehler M. Bosse and L. McMllan Non-Metrc Image-Based Renderng for Vdeo Stablzaton Proc. IEEE CVPR 200 Vol [5] A. Crmns P. Perez and K. Toyama Object Removal by Exemlar-Based Inantng Proc. IEEE CVPR 2003 Vol [6] M. A. Fschler and R. C. Bolles Random Samle Consensus: A Paradgm for Model Fttng wth Alcatons to Image Analyss and Automated Cartograhy CACM Vol. 24 No [7] J. Ja T.-P. Wu Y.-W. Ta and C.-K. Tang Vdeo Rearng Inference of Foreground and Background under Severe Occluson Proc. IEEE CVPR 2004 Vol

8 [8] A. Levn A. Zomet and Y. Wess Learnng How to Inant from Global Image Statstcs Proc. IEEE ICCV 2003 Vol [9] A. Ltvn J. Konrad and W. C. Karl Probablstc Vdeo Stablzaton usng Kalman Flterng and Mosackng Proc. SPIE EI 2003 Vol [0] D. G. Lowe Object Recognton from Local Scale- Invarant Features Proc. IEEE ICCV [] Y. Matsushta E. Ofek X. Tang and H.-Y. Shum Full- Frame Vdeo Stablzaton Proc. IEEE CVPR 2005 Vol [2] Z. Pan and C.-W. Ngo Structurng Home Vdeo by Snet Detecton and Pattern Parsng Proc. ACM MIR [3] K. A. Patwardhan G. Saro and M. Bertalmo Vdeo Inantng under Constraned Camera Moton IEEE TIP Vol. 6 No [4] P. Pérez M. Gangnet and A. Blake Posson Image Edtng Proc. ACM SIGGRAPH [5] T. Shrator Y. Matsushta X. Tang and S. B. Kang Vdeo Comleton by Moton Feld Transfer Proc. IEEE CVPR 2006 Vol [6] Y. Wexler E. Shechtman and M. Iran Sace-Tme Vdeo Comleton Proc. IEEE CVPR 2004 Vol Fg. : To row: Fve frames of the orgnal vdeo. Mddle row: Stablzed frames. Black areas show the mssng areas of the frames. Bottom row: Our result. Fg. 2: To row: Fve frames of the orgnal vdeo. Mddle row: Stablzed frames. Black areas show the mssng areas of the frames. Bottom row: Our result.