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CVPR
2000
IEEE
15 years 2 months ago
Adaptive Bayesian Recognition in Tracking Rigid Objects
We present a framework for tracking rigid objects based on an adaptive Bayesian recognition technique that incorporates dependencies between object features. At each frame we fin...
Yuri Boykov, Daniel P. Huttenlocher
CVPR
2012
IEEE
13 years 13 days ago
Coupling detection and data association for multiple object tracking
We present a novel framework for multiple object tracking in which the problems of object detection and data association are expressed by a single objective function. The framewor...
Zheng Wu, Ashwin Thangali, Stan Sclaroff, Margrit ...
ICIP
2000
IEEE
15 years 11 months ago
Mean Shift and Optimal Prediction for Efficient Object Tracking
A new paradigm for the efficient color-based tracking of objects seen from a moving camera is presented. The proposed technique employs the mean shift analysis to derive the targe...
Dorin Comaniciu, Visvanathan Ramesh
CDC
2008
IEEE
143views Control Systems» more  CDC 2008»
15 years 4 months ago
Particle filtering using multiple cross-correlations for tracking occluded objects in cluttered scenes
— This paper is concerned with the tracking of partially or entirely occluded objects in a video sequence. We propose certain modifications to the template matching approach, whi...
Arie Nakhmani, Allen Tannenbaum
ICMCS
2007
IEEE
191views Multimedia» more  ICMCS 2007»
15 years 4 months ago
Variable Number of "Informative" Particles for Object Tracking
Particle filter is a sequential Monte Carlo method for object tracking in a recursive Bayesian filtering framework. The efficiency and accuracy of the particle filter depends on t...
Yu Huang, Joan Llach