IEEE Trans Pattern Anal Mach Intell - Computing Smooth Time Trajectories for Camera and Deformable Shape in Structure from Motion with Occlusion.

Tópicos

{ motion(1329) object(1292) video(1091) }
{ method(984) reconstruct(947) comput(926) }
{ problem(2511) optim(1539) algorithm(950) }
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{ method(2212) result(1239) propos(1039) }
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Resumo

We address the classical computer vision problems of rigid and nonrigid structure from motion (SFM) with occlusion. We assume that the columns of the input observation matrix W describe smooth 2D point trajectories over time. We then derive a family of efficient methods that estimate the column space of W using compact parameterizations in the Discrete Cosine Transform (DCT) domain. Our methods tolerate high percentages of missing data and incorporate new models for the smooth time trajectories of 2D-points, affine and weak-perspective cameras, and 3D deformable shape. We solve a rigid SFM problem by estimating the smooth time trajectory of a single camera moving around the structure of interest. By considering a weak-perspective camera model from the outset, we directly compute euclidean 3D shape reconstructions without requiring postprocessing steps such as euclidean upgrade and bundle adjustment. Our results on real SFM data sets with high percentages of missing data compared positively to those in the literature. In nonrigid SFM, we propose a novel 3D shape trajectory approach that solves for the deformable structure as the smooth time trajectory of a single point in a linear shape space. A key result shows that, compared to state-of-the-art algorithms, our nonrigid SFM method can better model complex articulated deformation with higher frequency DCT components while still maintaining the low-rank factorization constraint. Finally, we also offer an approach for nonrigid SFM when W is presented with missing data.

Resumo Limpo

address classic comput vision problem rigid nonrigid structur motion sfm occlus assum column input observ matrix w describ smooth d point trajectori time deriv famili effici method estim column space w use compact parameter discret cosin transform dct domain method toler high percentag miss data incorpor new model smooth time trajectori dpoint affin weakperspect camera d deform shape solv rigid sfm problem estim smooth time trajectori singl camera move around structur interest consid weakperspect camera model outset direct comput euclidean d shape reconstruct without requir postprocess step euclidean upgrad bundl adjust result real sfm data set high percentag miss data compar posit literatur nonrigid sfm propos novel d shape trajectori approach solv deform structur smooth time trajectori singl point linear shape space key result show compar stateoftheart algorithm nonrigid sfm method can better model complex articul deform higher frequenc dct compon still maintain lowrank factor constraint final also offer approach nonrigid sfm w present miss data

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