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» Adaptive Background Mixture Models for Real-Time Tracking
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CVPR
1998
IEEE
14 years 9 months ago
Background Modeling for Segmentation of Video-Rate Stereo Sequences
Stereo sequences promise to be a powerful method for segmenting images for applications such as tracking human figures. We present a method of statistical background modeling for ...
Christopher K. Eveland, Kurt Konolige, Robert C. B...
ICMCS
2006
IEEE
215views Multimedia» more  ICMCS 2006»
14 years 1 months ago
Experiential Sampling based Foreground/Background Segmentation for Video Surveillance
Segmentation of foreground and background has been an important research problem arising out of many applications including video surveillance. A method commonly used for segmenta...
Pradeep K. Atrey, Vinay Kumar, Anurag Kumar, Mohan...
BMCBI
2008
132views more  BMCBI 2008»
13 years 7 months ago
Mixture models for analysis of melting temperature data
Background: In addition to their use in detecting undesired real-time PCR products, melting temperatures are useful for detecting variations in the desired target sequences. Metho...
Christoffer Nellåker, Fredrik Uhrzander, Joa...
ICASSP
2011
IEEE
12 years 11 months ago
Detecting moving objects from dynamic background with shadow removal
Background subtraction is commonly used to detect foreground objects in video surveillance. Traditional background subtraction methods are usually based on the assumption that the...
Shih-Chieh Wang, Te-Feng Su, Shang-Hong Lai
MVA
2008
125views Computer Vision» more  MVA 2008»
13 years 7 months ago
Pearson-based mixture model for color object tracking
To track objects in video sequences, many studies have been done to characterize the target with respect to its color distribution. Most often, the Gaussian Mixture Model (GMM) is ...
William Ketchantang, Stéphane Derrode, Lion...