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» Integration of Background Modeling and Object Tracking
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ICRA
2006
IEEE
113views Robotics» more  ICRA 2006»
15 years 4 months ago
Integration of Dependent Bayesian Filters for Robust Tracking
— Robotics applications based on computer vision algorithms are highly constrained to indoor environments where conditions may be controlled. The development of robust visual alg...
Francesc Moreno-Noguer, Alberto Sanfeliu, Dimitris...
73
Voted
WCE
2007
14 years 11 months ago
Motion Detection Based On Accumulative Optical Flow and Double Background Filtering
—Moving object detection is very important for video surveillance. In this paper, we present a new real time motion detection algorithm that is based on the integration of accumu...
Nan Lu, Jihong Wang, Li Yang, Q. Henry Wu
IVC
2006
183views more  IVC 2006»
14 years 10 months ago
Augmented tracking with incomplete observation and probabilistic reasoning
An on-line algorithm for multi-object tracking is presented for monitoring a real-world scene from a single fixed camera. Potential objects are detected with adaptive backgrounds ...
Ming Xu, Tim Ellis
ICIP
2009
IEEE
14 years 8 months ago
An efficient and robust sequential algorithm for background estimation in video surveillance
Many computer vision algorithms such as object tracking and event detection assume that a background model of the scene under analysis is known. However, in many practical circums...
Vikas Reddy, Conrad Sanderson, Brian C. Lovell
ICPR
2008
IEEE
15 years 11 months ago
Variational Maximum A Posteriori model similarity and dissimilarity matching
A new variational Maximum A Posteriori (MAP) contextual modeling approach is presented that minimizes the product of two ratios: (a) the ratio of the model distribution to the dis...
John Chiverton, Majid Mirmehdi, Xianghua Xie