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» An Adaptive Bayesian Technique for Tracking Multiple Objects
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CVPR
2005
IEEE
14 years 9 months ago
Kernel-Based Bayesian Filtering for Object Tracking
Particle filtering provides a general framework for propagating probability density functions in non-linear and non-Gaussian systems. However, the algorithm is based on a Monte Ca...
Bohyung Han, Ying Zhu, Dorin Comaniciu, Larry S. D...
CVPR
2008
IEEE
14 years 9 months ago
Multi-object shape estimation and tracking from silhouette cues
This paper deals with the 3D shape estimation from silhouette cues of multiple moving objects in general indoor or outdoor 3D scenes with potential static obstacles, using multipl...
Li Guan, Jean-Sébastien Franco, Marc Pollef...
TSMC
2008
147views more  TSMC 2008»
13 years 7 months ago
Tracking of Multiple Targets Using Online Learning for Reference Model Adaptation
Recently, much work has been done in multiple ob-4 ject tracking on the one hand and on reference model adaptation5 for a single-object tracker on the other side. In this paper, we...
Franz Pernkopf
ICASSP
2011
IEEE
12 years 11 months ago
Robust video object tracking based on multiple kernels with projected gradients
In kernel-based video object tracking, the use of single kernel often suffers from the occlusion. In order to provide more robust tracking performance, multiple inter-related kern...
Chun-Te Chu, Jenq-Neng Hwang, Hung-I. Pai, Kung-Mi...
WSCG
2004
232views more  WSCG 2004»
13 years 9 months ago
Robust Tracking of Athletes Using Multiple Features of Multiple Views
This paper presents a robust and reconfigurable object tracker that integrates multiple visual features from multiple views. The tandem modular architecture stepwise refines the e...
Toshihiko Misu, Seiichi Gohshi, Yoshinori Izumi, Y...