The key issue in motion estimation and tracking an object over a fieqwnce of images is establishing correspondpncp betwen the features of the object in the different images of t hr sequence. For range image spquences, this problem translates into finding a match between the surface segments in a pair of ranRe images of the scene. This paper considers the problem of establishing rorrespondences hetwn surlaces in a sequence oi range images. N'e prpaent a novel procedure for finding correspondence and show the results an real range image sequences. h graph search procedur~ forms the basis lar the algorithm that computes the rorr~spondcnce bvtwwn surfaces. The solutinn usen grometrical and topological information derived from th~ sr~nes to direct t h~ search procedure. Fundamental ta our strategy to match features over a seqrlence of ranw images is a hypergraph representation of the scenes. Two scenPs arr modcled as hyp~rgraphs and the hyperedges are matched using a suh-graph isomorphism algorithm. The hietarrhicd rrprrsentalion of hypergraphs not only rrdures the search space significantly, brtt also facilitates the encoding of the topological and geometrical information. R~rth~r. we present a sub-hypcrgrap h isomorphism pror~di~rp to ~~tahlish the corr~spond~nces between the surfar~ patchrs and drrnonstrate the al~orit hrn an different typ~s of tral ranp imagt. spquences. We present res~lfts tha~ show that the algorithm is robust and performs well in prPaPncP of occlusions and incorrect segmentations. The key issue in motion stir nation and tracking an object owr a SequPncP of images is establishing correspondcnce between the features of the object in the different ima~es of the sequence. Fn this paper we deal with the tracking of objerts in a sequence of range images to estimate t hc motion of the camera (range smsor) in the environment. Rangc irnap;es sense the surfacr of the objects, so it is natural to use stirface a~grnents as the features of interest: this translates the tracking of objects into finding a matrh h~rw~cn the surface segments in a pair of ranRe images of I hp scenp. This paper considers the finding OF correspondences between aurfac~a in a sequence of range image<. Finding rnrrespondenrp or a matrh bptween features is not isolat~d to ohject tracking, but ia also centrd to other computer vision tasks ~ncEuding navigation. ohjerl recognition, target tracking, and map building, We present a novel procedi~r~ for estabIishing correspondence and slrow tho rcsults on real range image sequences. h graph search procedure forms the hnqis far the alprit hrn that computes t hc correspondence betwwn surfaces. The solution uses geometrical and topolo~ical information derived From the scenes to direct the search procedure. In general, the input to the matching algorithm is the output from a s~grnentation al~orithm that partitions the image into surface srgments. The performance of the matching depends greatly on the results or the segmentation algorithms. Incnrrpct s~grn~ntatinn causes poor estimation of the surface parameters and aff~ctfi the performance of the match in^ algoritlim. We address this iasuc and obtain a ~olotion that is rohusr and able to handle occli~sinns of fiurfaces, noisr in data, and incorrect segmentation from a segment ation alaorit hm. In the present implementation,
['Bikash Sabata', 'J. K. Aggarwal']
CORRESPONDENCE OF SURFACES IN A SEQUENCE OF RANGE IMAGES FOR MOTION ESTIMATION AND TRACKING