Multicamera People Tracking with a Probabilistic Occupancy Map
École Polytechnique Fédérale de Lausanne
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Abstract
Given two to four synchronized video streams taken at eye level and from different angles, we show that we can effectively combine a generative model with dynamic programming to accurately follow up to six individuals across thousands of frames in spite of significant occlusions and lighting changes. In addition, we also derive metrically accurate trajectories for each one of them. Our contribution is twofold. First, we demonstrate that our generative model can effectively handle occlusions in each time frame independently, even when the only data available comes from the output of a simple background subtraction algorithm and when the number of individuals is unknown a priori. Second, we show that…
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4Topics & keywords
Topics
Keywords
- Computer science
- Background subtraction
- Artificial intelligence
- A priori and a posteriori
- Probabilistic logic
- Heuristic
- Generative model
- Frame (networking)
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