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» An optical flow probabilistic observation model for tracking
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ICIP
2008
IEEE
14 years 2 months ago
An adaptive background model initialization algorithm with objects moving at different depths
Background subtraction is an essential element in most object tracking and video surveillance systems. The success of this low-level processing step is highly dependent on the qua...
Chia-Chih Chen, J. K. Aggarwal
CVPR
2003
IEEE
14 years 9 months ago
Tracking Appearances with Occlusions
Occlusion is a difficult problem for appearance-based target tracking, especially when we need to track multiple targets simultaneously and maintain the target identities during t...
Ying Wu, Ting Yu, Gang Hua
ICML
2006
IEEE
14 years 8 months ago
Combining discriminative features to infer complex trajectories
We propose a new model for the probabilistic estimation of continuous state variables from a sequence of observations, such as tracking the position of an object in video. This ma...
David A. Ross, Simon Osindero, Richard S. Zemel
ICCV
2003
IEEE
14 years 9 months ago
Tracking Articulated Body by Dynamic Markov Network
A new method for visual tracking of articulated objects is presented. Analyzing articulated motion is challenging because the dimensionality increase potentially demands tremendou...
Ying Wu, Gang Hua, Ting Yu
DAGM
2006
Springer
13 years 11 months ago
Diffusion-Like Reconstruction Schemes from Linear Data Models
In this paper we extend anisotropic diffusion with a diffusion tensor to be applicable to data that is well modeled by linear models. We focus on its variational theory, and invest...
Hanno Scharr