Search Results for author:
Found 2 papers, 0 papers with code
Linear Complexity Gibbs Sampling for Generalized Labeled Multi-Bernoulli Filtering
Specifically, we propose a tempered Gibbs sampler that exploits the structure of the GLMB filtering density to achieve an $\mathcal{O}(T(P+M))$ complexity, where $T$ is the number of iterations of the algorithm, $P$ and $M$ are the number hypothesized objects and measurements.
A Bayesian Filter for Multi-view 3D Multi-object Tracking with Occlusion Handling
This paper proposes an online multi-camera multi-object tracker that only requires monocular detector training, independent of the multi-camera configurations, allowing seamless extension/deletion of cameras without retraining effort.
Ranked #7 on
Multi-Object Tracking
on Wildtrack
