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» Non-parametric Model for Background Subtraction
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ICIP
2004
IEEE
14 years 9 months ago
A fine-structure image/video quality measure using local statistics
An objective no-reference measure is presented to assess fine-structure image/video quality. It was designed to measure image/video quality for video surveillance applications, es...
Kyungnam Kim, Larry S. Davis
CAIP
2003
Springer
176views Image Analysis» more  CAIP 2003»
14 years 28 days ago
Evaluation of an Adaptive Composite Gaussian Model in Video Surveillance
Video surveillance systems seek to automatically identify events of interest in a variety of situations. Extracting a moving object from background is the most important step of t...
Qi Zang, Reinhard Klette
MVA
2002
188views Computer Vision» more  MVA 2002»
13 years 7 months ago
Adaptive Background Estimation for Object Tracking
2 Adaptive Background Model Tracking people has received considerable attention by computer vision researchers. Interest is motivated by the broad range of potential applications s...
Ryunosuke Itoh, Yoshio Iwai, Masahiko Yachida
TCSV
2008
148views more  TCSV 2008»
13 years 7 months ago
Modeling Background and Segmenting Moving Objects from Compressed Video
Abstract--Modeling background and segmenting moving objects are significant techniques for video surveillance and other video processing applications. Most existing methods of mode...
Weiqiang Wang, Jie Yang, Wen Gao
ACCV
2006
Springer
14 years 1 months ago
A Multiscale Co-linearity Statistic Based Approach to Robust Background Modeling
Background subtraction is an essential task in several static camera based computer vision systems. Background modeling is often challenged by spatio-temporal changes occurring due...
Prithwijit Guha, Dibyendu Palai, K. S. Venkatesh, ...