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TIP
2008
177views more  TIP 2008»
13 years 3 months ago
Visual Tracking in High-Dimensional State Space by Appearance-Guided Particle Filtering
Abstract--In this paper, we propose a new approach, appearance-guided particle filtering (AGPF), for high degree-of-freedom visual tracking from an image sequence. This method adop...
Wen-Yan Chang, Chu-Song Chen, Yong-Dian Jian
ICASSP
2011
IEEE
12 years 7 months ago
Particle algorithms for filtering in high dimensional state spaces: A case study in group object tracking
We briefly present the current state-of-the-art approaches for group and extended object tracking with an emphasis on particle methods which have high potential to handle complex...
Lyudmila Mihaylova, Avishy Carmi
CVPR
2001
IEEE
14 years 5 months ago
Automatic Partitioning of High Dimensional Search Spaces Associated with Articulated Body Motion Capture
Particle filters have proven to be an effective tool for visual tracking in non-gaussian, cluttered environments. Conventional particle filters however do not scale to the problem...
Jonathan Deutscher, Andrew J. Davison, Ian D. Reid
ICCV
2001
IEEE
14 years 5 months ago
People Tracking Using Hybrid Monte Carlo Filtering
Particle filters are used for hidden state estimation with nonlinear dynamical systems. The inference of 3-d human motion is a natural application, given the nonlinear dynamics of...
Kiam Choo, David J. Fleet
ICMCS
2007
IEEE
173views Multimedia» more  ICMCS 2007»
13 years 10 months ago
Tracking Multiple Objects using Probability Hypothesis Density Filter and Color Measurements
Most methods for multiple object tracking in video represent the state of multi-objects in a high dimensional joint state space. This leads to high computational complexity. This ...
Nam Trung Pham, Weimin Huang, Sim Heng Ong