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ICASSP
2011
IEEE
12 years 9 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
CVPR
2012
IEEE
11 years 8 months ago
Background modeling using adaptive pixelwise kernel variances in a hybrid feature space
Recent work on background subtraction has shown developments on two major fronts. In one, there has been increasing sophistication of probabilistic models, from mixtures of Gaussi...
Manjunath Narayana, Allen R. Hanson, Erik G. Learn...
CVPR
2012
IEEE
11 years 8 months ago
Incremental gradient on the Grassmannian for online foreground and background separation in subsampled video
It has recently been shown that only a small number of samples from a low-rank matrix are necessary to reconstruct the entire matrix. We bring this to bear on computer vision prob...
Jun He, Laura Balzano, Arthur Szlam
ICASSP
2009
IEEE
14 years 10 days ago
A semi-supervised learning approach to online audio background detection
We present a framework for audio background modeling of complex and unstructured audio environments. The determination of background audio is important for understanding and predi...
Selina Chu, Shrikanth S. Narayanan, C.-C. Jay Kuo
CVPR
1998
IEEE
14 years 7 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...