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» A Linear Programming Approach for Multiple Object Tracking
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CVPR
1999
IEEE
14 years 9 months ago
A Multiple Hypothesis Approach to Figure Tracking
This paper describes a probabilistic multiple-hypothesis framework for tracking highly articulated objects. In this framework, the probability density of the tracker state is repr...
Tat-Jen Cham, James M. Rehg
ISSRE
2007
IEEE
13 years 9 months ago
Improving Constraint-Based Testing with Dynamic Linear Relaxations
Constraint-Based Testing (CBT) is the process of generating test cases against a testing objective by using constraint solving techniques. In CBT, testing objectives are given und...
Tristan Denmat, Arnaud Gotlieb, Mireille Ducass&ea...
ICCV
2001
IEEE
14 years 9 months ago
Continuous Global Evidence-Based Bayesian Modality Fusion for Simultaneous Tracking of Multiple Objects
Robust, real-time tracking of objects from visual data requires probabilistic fusion of multiple visual cues. Previous approaches have either been ad hoc or relied on a Bayesian n...
Jamie Sherrah, Shaogang Gong
IROS
2006
IEEE
155views Robotics» more  IROS 2006»
14 years 1 months ago
Multiple Hypothesis Tracking of Clusters of People
— Mobile robots operating in populated environments typically can improve their service and navigation behavior when they know where people are in their vicinity and in which dir...
Manuel Mucientes, Wolfram Burgard
CVPR
2006
IEEE
14 years 9 months ago
Fusion of Detection and Matching Based Approaches for Laser Based Multiple People Tracking
Most of visual tracking algorithms have been achieved by matching-based searching strategies or detection-based data association algorithms. In this paper, our objective is to ana...
Jinshi Cui, Huijing Zhao, Ryosuke Shibasaki