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About this paper
Yuxiang Zhang, Liang An, Tao Yu, Xiu Li, Kun Li, Yebin Liu
A real-time multi-person motion capture system leveraging a 4D association graph unifies per-view parsing, cross-view matching, and temporal tracking for multi-camera video input. The system achieves 30 frames per second for up to 5 persons, demonstrating 97.6% PCP on the Shelf dataset and improved precision on a new challenging multi-person dataset.
Key insights
- Unifying per-view parsing, cross-view matching, and temporal tracking in a single 4D graph allows constraints to mutually reinforce, significantly enhancing robustness against noisy detections and occlusions.
- Decomposing the complex 4D association into efficient sub-problems, specifically 4D limb bundle parsing and skeleton assembling, is crucial for achieving real-time performance in multi-person scenarios.
- Precise low-level 2D features, combined with geometric and temporal consistency from the 4D graph, can achieve high accuracy without extensive reliance on high-level appearance information.
Summary by alphaXiv.
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