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» Integration of Background Modeling and Object Tracking
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ICMCS
2006
IEEE
111views Multimedia» more  ICMCS 2006»
13 years 10 months ago
Integration of Background Modeling and Object Tracking
Background model and tracking became critical components for many vision-based applications. Typically, background modeling and object tracking are mutually independent in many ap...
Yu-Ting Chen, Chu-Song Chen, Yi-Ping Hung
ICCV
2005
IEEE
14 years 6 months ago
Integration of Conditionally Dependent Object Features for Robust Figure/Background Segmentation
We propose a new technique for fusing multiple cues to robustly segment an object from its background in video sequences that suffer from abrupt changes of both illumination and p...
Francesc Moreno-Noguer, Alberto Sanfeliu, Dimitris...
ICCV
2001
IEEE
14 years 6 months ago
Plan-View Trajectory Estimation with Dense Stereo Background Models
In a known environment, objects may be tracked in multiple views using a set of background models. Stereo-based models can be illumination-invariant, but often have undefined valu...
Trevor Darrell, David Demirdjian, Neal Checka, Ped...
ICMCS
2007
IEEE
124views Multimedia» more  ICMCS 2007»
13 years 11 months ago
Robust Video Object Segmentation Based on K-Means Background Clustering and Watershed in Ill-Conditioned Surveillance Systems
A robust video object segmentation algorithm for complex conditions in surveillance systems is proposed in this paper. This algorithm contains an unsupervised K-Means background c...
Tse-Wei Chen, Shou-Chieh Hsu, Shao-Yi Chien
ICIP
2002
IEEE
14 years 6 months ago
Likelihood-based object detection and object tracking using color histograms and EM
The topic of this paper is the integration of Expectation Maximization (EM) background modeling and template matching using color histograms as templates to improve person trackin...
Paul J. Withagen, Klamer Schutte, Frans C. A. Groe...