The Visual Hull Concept for Silhouette-Based Image Understanding
IEEE Transactions on Pattern Analysis and Machine Intelligence
Human Body Model Acquisition and Tracking Using Voxel Data
International Journal of Computer Vision
Combining 2D Feature Tracking and Volume Reconstruction for Online Video-Based Human Motion Capture
PG '02 Proceedings of the 10th Pacific Conference on Computer Graphics and Applications
Real-Time Markerless Human Body Tracking Using Colored Voxels and 3-D Blobs
ISMAR '04 Proceedings of the 3rd IEEE/ACM International Symposium on Mixed and Augmented Reality
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
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Voxel reconstruction has received increasing interest in recent times, driven by the need for efficient reconstructions of real world scenes from video images. The voxel model has proven useful for activity recognition and motion capture technologies. However most current voxel reconstruction algorithms operate on a fairly small 3-D real world volume and only allow for a single person to be reconstructed. In this paper we present SparseSPOT, an extension of the SPOT voxel reconstruction algorithm, that enables real-time reconstruction of multiple humans within a large environment. We compare SparseSPOT to SPOT and show (by extensive experimental evaluation) that the former achieves superior real time performance.