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» Adaptive object tracking by learning background context
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ICCV
2009
IEEE
13 years 6 months ago
Realtime background subtraction from dynamic scenes
This paper examines the problem of moving object detection. More precisely, it addresses the difficult scenarios where background scene textures in the video might change over tim...
Li Cheng, Minglun Gong
ISDA
2010
IEEE
13 years 5 months ago
Self-adaptive Gaussian mixture models for real-time video segmentation and background subtraction
The usage of Gaussian mixture models for video segmentation has been widely adopted. However, the main difficulty arises in choosing the best model complexity. High complex models ...
Nicola Greggio, Alexandre Bernardino, Cecilia Lasc...
CVPR
1999
IEEE
1071views Computer Vision» more  CVPR 1999»
14 years 10 months ago
Adaptive Background Mixture Models for Real-Time Tracking
A common method for real-time segmentation of moving regions in image sequences involves "background subtraction," or thresholding the error between an estimate of the i...
Chris Stauffer, W. Eric L. Grimson
ICIP
2008
IEEE
14 years 3 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

Publication
264views
13 years 5 months ago
Combined feature evaluation for adaptive visual object tracking
Existing visual tracking methods are challenged by object and background appearance variations, which often occur in a long duration tracking. In this paper, we propose a combined ...
Zhenjun Han, Qixiang Ye, Jianbin Jiao