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AVSS
2009
IEEE
13 years 9 months ago
Robust Vehicle Detection for Tracking in Highway Surveillance Videos Using Unsupervised Learning
This paper presents a novel approach to vehicle detection in highway surveillance videos. This method incorporates well-studied computer vision and machine learning techniques to ...
Birgi Tamersoy, Jake K. Aggarwal
TCSV
2010
13 years 3 months ago
Video Foreground Detection Based on Symmetric Alpha-Stable Mixture Models
Background subtraction (BS) is an efficient technique for detecting moving objects in video sequences. A simple BS process involves building a model of the background and extractin...
Harish Bhaskar, Lyudmila Mihaylova, Alin Achim
CVPR
2006
IEEE
14 years 10 months ago
A Framework for Feature Selection for Background Subtraction
Background subtraction is a widely used paradigm to detect moving objects in video taken from a static camera and is used for various important applications such as video surveill...
Toufiq Parag, Ahmed M. Elgammal, Anurag Mittal
AVSS
2008
IEEE
13 years 10 months ago
Evaluation of Background Subtraction Algorithms with Post-Processing
Processing a video stream to segment foreground objects from the background is a critical first step in many computer vision applications. Background subtraction (BGS) is a common...
Donovan H. Parks, Sidney Fels
CVPR
2008
IEEE
13 years 10 months ago
An integrated background model for video surveillance based on primal sketch and 3D scene geometry
This paper presents a novel integrated background model for video surveillance. Our model uses a primal sketch representation for image appearance and 3D scene geometry to capture...
Wenze Hu, Haifeng Gong, Song Chun Zhu, Yongtian Wa...