International Journal of Computer Vision
Learning Articulated Structure and Motion
International Journal of Computer Vision
Enhanced model selection for motion segmentation
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Enhanced Local Subspace Affinity for feature-based motion segmentation
Pattern Recognition
Motion segmentation using the hadamard product and spectral clustering
WMVC'09 Proceedings of the 2009 international conference on Motion and video computing
Multi-scale 2D tracking of articulated objects using hierarchical spring systems
Pattern Recognition
5D motion subspaces for planar motions
ECCV'10 Proceedings of the 11th European conference on computer vision conference on Computer vision: Part III
Adaptive motion segmentation algorithm based on the principal angles configuration
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part III
3D object recognition based on canonical angles between shape subspaces
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part IV
Spatio-temporal extraction of articulated models in a graph pyramid
GbRPR'11 Proceedings of the 8th international conference on Graph-based representations in pattern recognition
Hierarchical spatio-temporal extraction of models for moving rigid parts
Pattern Recognition Letters
Skin colour segmentation based 2D and 3D human pose modelling using Discrete Wavelet Transform
Pattern Recognition and Image Analysis
Optimal Metric Projections for Deformable and Articulated Structure-from-Motion
International Journal of Computer Vision
A unified view on deformable shape factorizations
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part VI
Learning spatially-smooth mappings in non-rigid structure from motion
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part IV
Multilinear Factorizations for Multi-Camera Rigid Structure from Motion Problems
International Journal of Computer Vision
Recursive non-rigid structure from motion with online learned shape prior
Computer Vision and Image Understanding
Occlusion-aware multi-view reconstruction of articulated objects for manipulation
Robotics and Autonomous Systems
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Recovering articulated shape and motion, especially human body motion, from video is a challenging problem with a wide range of applications in medical study, sport analysis and animation, etc. Previous work on articulated motion recovery generally requires prior knowledge of the kinematic chain and usually does not concern the recovery of the articulated shape. The non-rigidity of some articulated part, e.g. human body motion with nonrigid facial motion, is completely ignored. We propose a factorization-based approach to recover the shape, motion and kinematic chain of an articulated object with nonrigid parts altogether directly from video sequences under a unified framework. The proposed approach is based on our modeling of the articulated non-rigid motion as a set of intersecting motion subspaces. A motion subspace is the linear subspace of the trajectories of an object. It can model a rigid or non-rigid motion. The intersection of two motion subspaces of linked parts models the motion of an articulated joint or axis. Our approach consists of algorithms for motion segmentation, kinematic chain building, and shape recovery. It handles outliers and can be automated. We test our approach through synthetic and real experiments and demonstrate how to recover articulated structure with non-rigid parts via a single-view camera without prior knowledge of its kinematic chain.