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» A Probabilistic Framework for Combining Tracking Algorithms
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ICCV
2007
IEEE
14 years 9 months ago
Robust Visual Tracking Using the Time-Reversibility Constraint
Visual tracking is a very important front-end to many vision applications. We present a new framework for robust visual tracking in this paper. Instead of just looking forward in ...
Hao Wu, Rama Chellappa, Aswin C. Sankaranarayanan,...
CIKM
2006
Springer
13 years 11 months ago
A probabilistic relevance propagation model for hypertext retrieval
A major challenge in developing models for hypertext retrieval is to effectively combine content information with the link structure available in hypertext collections. Although s...
Azadeh Shakery, ChengXiang Zhai
AVSS
2006
IEEE
13 years 11 months ago
Classification-Based Likelihood Functions for Bayesian Tracking
The success of any Bayesian particle filtering based tracker relies heavily on the ability of the likelihood function to discriminate between the state that fits the image well an...
Chunhua Shen, Hongdong Li, Michael J. Brooks
CVIU
2006
142views more  CVIU 2006»
13 years 7 months ago
Robust target detection and tracking through integration of motion, color, and geometry
Vision-based tracking is a basic elementary task in many computer vision-based applications such as video surveillance and monitoring, sensing and navigation in robotics, video co...
Harini Veeraraghavan, Paul R. Schrater, Nikolaos P...
ICPR
2006
IEEE
14 years 8 months ago
Boosted Markov Chain Monte Carlo Data Association for Multiple Target Detection and Tracking
In this paper, we present a probabilistic framework for automatic detection and tracking of objects. We address the data association problem by formulating the visual tracking as ...
Bo Wu, Gérard G. Medioni, Isaac Cohen, Qian...