Monocular 3D tracking of multiple interacting targets
Tatsuya Osawa, Kyoko Sudo, Hiroyuki Arai, Hideki Koike · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition · 2008
In this paper, we present a new approach based on Markov Chain Monte Carlo(MCMC) for the stable monocular tracking of variable interacting targets in 3D space. The crucial problem with monocular tracking multiple targets is that mutual occlusions on the 2D image cause target conflict (change ID, merge targetshellip). We focus on the fact that multiple targets cannot occupy the same position in 3D space and propose to track multiple interacting targets using relative position of targets in 3D space. Experiments show that our system can stably track multiple humans that are interacting with each other.