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» A Multiple Hypothesis Approach to Figure Tracking
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CVPR
2007
IEEE
14 years 9 months ago
Tracking Large Variable Numbers of Objects in Clutter
We propose statistical data association techniques for visual tracking of enormously large numbers of objects. We do not assume any prior knowledge about the numbers involved, and...
Margrit Betke, Diane E. Hirsh, Angshuman Bagchi, N...
JMM2
2006
146views more  JMM2 2006»
13 years 7 months ago
Probabilistic Algorithms, Integration, and Empirical Evaluation for Disambiguating Multiple Selections in Frustum-Based Pointing
There are a few fundamental pointing-based user interface techniques for performing selections in 3D environments. One of these techniques is ray pointing, which makes selections b...
Greg S. Schmidt, Dennis G. Brown, Erik B. Tomlin, ...
ICIP
2007
IEEE
14 years 9 months ago
MAP Particle Selection in Shape-Based Object Tracking
The Bayesian filtering for recursive state estimation and the shape-based matching methods are two of the most commonly used approaches for target tracking. The Multiple Hypothesi...
Alessio Dore, Carlo S. Regazzoni, Mirko Musso
CVPR
2006
IEEE
14 years 9 months ago
Modeling Correspondences for Multi-Camera Tracking Using Nonlinear Manifold Learning and Target Dynamics
Multi-camera tracking systems often must maintain consistent identity labels of the targets across views to recover 3D trajectories and fully take advantage of the additional info...
Vlad I. Morariu, Octavia I. Camps
AMFG
2003
IEEE
148views Biometrics» more  AMFG 2003»
14 years 19 days ago
Multi-Modal Face Tracking Using Bayesian Network
This paper presents a Bayesian network based multimodal fusion method for robust and real-time face tracking. The Bayesian network integrates a prior of second order system dynami...
Fang Liu, Xueyin Lin, Stan Z. Li, Yuanchun Shi