How Far 3D Shapes Can Be Understood from 2D Silhouettes
IEEE Transactions on Pattern Analysis and Machine Intelligence
Human Body Model Acquisition and Tracking Using Voxel Data
International Journal of Computer Vision
Similarity Search in High Dimensions via Hashing
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
The Aware Home: A Living Laboratory for Ubiquitous Computing Research
CoBuild '99 Proceedings of the Second International Workshop on Cooperative Buildings, Integrating Information, Organization, and Architecture
Fast Pose Estimation with Parameter-Sensitive Hashing
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Information Theory, Inference & Learning Algorithms
Information Theory, Inference & Learning Algorithms
Discriminative Density Propagation for 3D Human Motion Estimation
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Full Body Tracking from Multiple Views Using Stochastic Sampling
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Conditional Random People: Tracking Humans with CRFs and Grid Filters
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Proceedings of the 3rd International Universal Communication Symposium
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In this paper, we present a novel framework to recover human body pose on multi camera systems. Our framework leverages 3D voxel data, which are reconstructed from multi-camera systems. The use of voxel data leads to viewpoint-free estimation, which benefits in that reconstruction of a training model is needless in different multicamera arrangements. Other notable aspects of our approach are real-time ensuring speed (up to 30 fps), flexibility towards various complex motions and environments. We treat the pose estimation problem as estimating human pose label from the voxel features and tackle this by example based approach. To ensure the real-time speed and to improve precision of pose estimation, a newly fast and robust near-neighbor search metric is installed prior to the evaluation process, what we call CSI-PSH. We demonstrate the effectiveness of our approach with experiments on both synthetic and real image sequences.