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» SVD based Kalman particle filter for robust visual tracking
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ICPR
2008
IEEE
14 years 5 months ago
SVD based Kalman particle filter for robust visual tracking
Object tracking is one of the most important tasks in computer vision. The unscented particle filter algorithm has been extensively used to tackle this problem and achieved a grea...
Qingdi Wei, Weiming Hu, Xi Li, Xiaoqin Zhang, Yang...
PAMI
2006
182views more  PAMI 2006»
13 years 4 months ago
Multicue HMM-UKF for Real-Time Contour Tracking
We propose an HMM model for contour detection based on multiple visual cues in spatial domain and improve it by joint probabilistic matching to reduce background clutter. It is fu...
Yunqiang Chen, Yong Rui, Thomas S. Huang
AROBOTS
2010
194views more  AROBOTS 2010»
13 years 2 months ago
Computationally efficient solutions for tracking people with a mobile robot: an experimental evaluation of Bayesian filters
Abstract Modern service robots will soon become an essential part of modern society. As they have to move and act in human environments, it is essential for them to be provided wit...
Nicola Bellotto, Huosheng Hu
ICIP
2005
IEEE
14 years 6 months ago
Augmented particle filtering for efficient visual tracking
Visual tracking is one of the key tasks in computer vision. The particle filter algorithm has been extensively used to tackle this problem due to its flexibility. However the conv...
Chunhua Shen, Michael J. Brooks, Anton van den Hen...
CVPR
2008
IEEE
14 years 6 months ago
Sequential particle swarm optimization for visual tracking
Visual tracking usually involves an optimization process for estimating the motion of an object from measured images in a video sequence. In this paper, a new evolutionary approac...
Xiaoqin Zhang, Weiming Hu, Stephen J. Maybank, Xi ...