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» An Object Tracking Scheme Based on Local Density
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CVPR
2004
IEEE
14 years 7 months ago
Incremental Density Approximation and Kernel-Based Bayesian Filtering for Object Tracking
Statistical density estimation techniques are used in many computer vision applications such as object tracking, background subtraction, motion estimation and segmentation. The pa...
Bohyung Han, Dorin Comaniciu, Ying Zhu, Larry S. D...
ICCV
2005
IEEE
14 years 7 months ago
On-Line Density-Based Appearance Modeling for Object Tracking
Object tracking is a challenging problems in real-time computer vision due to variations of lighting condition, pose, scale, and view-point over time. However, it is exceptionally...
Bohyung Han, Larry S. Davis
CVPR
2005
IEEE
14 years 7 months ago
Kernel-Based Bayesian Filtering for Object Tracking
Particle filtering provides a general framework for propagating probability density functions in non-linear and non-Gaussian systems. However, the algorithm is based on a Monte Ca...
Bohyung Han, Ying Zhu, Dorin Comaniciu, Larry S. D...
SMI
2007
IEEE
192views Image Analysis» more  SMI 2007»
13 years 11 months ago
Multivariate Density-Based 3D Shape Descriptors
We address the 3D object retrieval problem using multivariate density-based shape descriptors. Considering the fusion of first and second order local surface information, we cons...
Ceyhun Burak Akgül, Bülent Sankur, Franc...
ICCV
2007
IEEE
14 years 7 months ago
Graph Based Discriminative Learning for Robust and Efficient Object Tracking
Object tracking is viewed as a two-class 'one-versusrest' classification problem, in which the sample distribution of the target is approximately Gaussian while the back...
Xiaoqin Zhang, Weiming Hu, Stephen J. Maybank, Xi ...