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ICIP
2007
IEEE
14 years 7 months ago
Multi-Modal Particle Filtering Tracking using Appearance, Motion and Audio Likelihoods
We propose a multi-modal object tracking algorithm that combines appearance, motion and audio information in a particle filter. The proposed tracker fuses at the likelihood level ...
Matteo Bregonzio, Murtaza Taj, Andrea Cavallaro

Publication
264views
13 years 2 months ago
Combined feature evaluation for adaptive visual object tracking
Existing visual tracking methods are challenged by object and background appearance variations, which often occur in a long duration tracking. In this paper, we propose a combined ...
Zhenjun Han, Qixiang Ye, Jianbin Jiao
ICIP
2002
IEEE
14 years 7 months ago
Template tracking using color invariant pixel features
In our method for tracking objects, appearance features are smoothed by robust and adaptive Kalman filters, one to each pixel, making the method robust against occlusions. While t...
Hieu Tat Nguyen, Arnold W. M. Smeulders
CVPR
2008
IEEE
14 years 7 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 ...
CVPR
2010
IEEE
14 years 1 months ago
Visual Object Tracking using Adaptive Correlation Filters
Although not commonly used, correlation filters can track complex objects through rotations, occlusions and other distractions at over 20 times the rate of current state-ofthe-ar...
David Bolme, J Ross Beveridge, Bruce Draper, Yui M...