Laura Leal-Taixé, Gerard Pons-Moll and Bodo Rosenhahn
We present a new algorithm to jointly track multiple objects in multi-view images. While this has been typically addressed separately in the past, we tackle the problem as a single global optimization.
We formulate this assignment problem as a min-cost problem by defining a graph structure that captures both temporal correlations between objects as well as spatial correlations enforced by the configuration of the cameras.
This leads to a complex combinatorial optimization problem that we solve using Dantzig-Wolfe decomposition and branching. Our formulation allows us to solve the problem of reconstruction and tracking in a single step by taking all available evidence into account.
In several experiments on multiple people tracking and 3D human pose tracking, we show our method outperforms state-of-the-art approaches.
You can download the paper here
The code for this paper is now available! Please cite the corresponding paper if you use this code.
You can also download the poster presented at the conference.
