Abstract
In this paper, we show how interacting and occluding targets can be tackled successfully within a Gaussian approximation. For that purpose, we develop a general expansion of the mean and covariance of the posterior and we consider a first order approximation of it. The proposed method differs from EKF in that neither a non-linear dynamical model nor a non-linear measurement vector to state relation have to be defined, so it works with any kind of interaction potential and likelihood. The approach has been tested on three sequences (10400, 2500, and 400 frames each one). The results show that our approach helps to reduce the number of failures without increasing too much the computation time with respect to methods that do not take into account target interactions.
| Original language | English |
|---|---|
| Pages (from-to) | 241-253 |
| Number of pages | 13 |
| Journal | Journal of Mathematical Imaging and Vision |
| Volume | 36 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - Mar 2010 |
ASJC Scopus subject areas
- Computer Vision and Pattern Recognition
- Modelling and Simulation
- Geometry and Topology
- Applied Mathematics
- Statistics and Probability
- Condensed Matter Physics
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