Reconstruction of articulated objects from point correspondences in a single uncalibrated image
Computer Vision and Image Understanding
Singularity Analysis for Articulated Object Tracking
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Tracking People with Twists and Exponential Maps
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Cardboard People: A Parameterized Model of Articulated Image Motion
FG '96 Proceedings of the 2nd International Conference on Automatic Face and Gesture Recognition (FG '96)
Inference of Human Postures by Classification of 3D Human Body Shape
AMFG '03 Proceedings of the IEEE International Workshop on Analysis and Modeling of Faces and Gestures
Fast Pose Estimation with Parameter-Sensitive Hashing
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Pictorial Structures for Object Recognition
International Journal of Computer Vision
Articulated Body Motion Capture by Stochastic Search
International Journal of Computer Vision
A Model-Based Approach for Estimating Human 3D Poses in Static Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recovering 3D Human Body Configurations Using Shape Contexts
IEEE Transactions on Pattern Analysis and Machine Intelligence
Real Time Limb Tracking with Adaptive Model Selection
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 04
Recovering human body configurations: combining segmentation and recognition
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
3D human pose from silhouettes by relevance vector regression
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Body-Part Templates for Recovery of 2D Human Poses under Occlusion
AMDO '08 Proceedings of the 5th international conference on Articulated Motion and Deformable Objects
Upper Body Detection and Tracking in Extended Signing Sequences
International Journal of Computer Vision
| Hi-index | 0.00 |
We propose a method to find candidate 2D articulated model configurations by searching for locally optimal configurations under a weak but computationally manageable fitness function. This is accomplished by first parameterizing a tree structure by its joints. Candidate configurations can then efficiently and exhaustively be assembled in a bottom-up manner. Working from the leaves of the tree to its root, we maintain a list of locally optimal, yet sufficiently distinct candidate configurations for the body pose. We then adapt this algorithm for use on a sequence of images by considering configurations that are either near their position in the previous frame or overlap areas of interest in subsequent frames. This way, the number of partial configurations generated and evaluated significantly reduces while both smooth and abrupt motions can be accommodated. This approach is validated on test and standard datasets.