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2011
IEEE

Detecting moving objects from dynamic background with shadow removal

8 years 7 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 background is stationary. However, they are not applicable to dynamic background, whose background images change over time. In this paper, we propose an adaptive Local-Patch Gaussian Mixture Model (LPGMM) as the dynamic background model for detecting moving objects from video with dynamic background. Then, the SVM classification is employed to discriminate between foreground objects and shadow regions. Finally, we show some experimental results on several video sequences to demonstrate the effectiveness and robustness of the proposed method.
Shih-Chieh Wang, Te-Feng Su, Shang-Hong Lai
Added 20 Aug 2011
Updated 20 Aug 2011
Type Journal
Year 2011
Where ICASSP
Authors Shih-Chieh Wang, Te-Feng Su, Shang-Hong Lai
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