CSDL Home IEEE Transactions on Pattern Analysis & Machine Intelligence 2011 vol.33 Issue No.10 - October
Computing Smooth Time Trajectories for Camera and Deformable Shape in Structure from Motion with Occlusion
Issue No.10 - October (2011 vol.33)
A. M. Martinez , Dept. of Electr. & Comput. Eng., Ohio State Univ., Columbus, OH, USA
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TPAMI.2011.50
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.
shape recognition, cameras, computer graphics, computer vision, discrete cosine transforms, matrix decomposition, motion estimation, missing data, smooth time trajectories, 3D deformable shape, occlusion, computer vision, structure from motion, input observation matrix, compact parameterizations, discrete cosine transform, weak-perspective cameras, motion estimation, 3D shape reconstructions, 3D shape trajectory, low-rank factorization constraint, Cameras, Shape, Discrete cosine transforms, Three dimensional displays, Trajectory, Jacobian matrices, Periodic structures, shape trajectory., Structure from motion, matrix factorization, missing data, camera trajectory
A. M. Martinez, "Computing Smooth Time Trajectories for Camera and Deformable Shape in Structure from Motion with Occlusion", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol.33, no. 10, pp. 2051-2065, October 2011, doi:10.1109/TPAMI.2011.50