JOURNAL ARTICLE

Motion-based background subtraction

Ming Zhang

Year: 2009 Journal:   Optical Engineering Vol: 48 (12)Pages: 127004-127004   Publisher: SPIE

Abstract

A framework is suggested to segment the foreground in image sequences using background subtraction based on the reconstructed background image for each frame. First, the consecutive frames are taken as inputs for a motion estimation algorithm to calculate the motion vector between frames. Second, an incomplete background image can be achieved by cutting moving parts from origin images. Then, all the incomplete background images from the same sequence can be used to model the background by probabilistic principle component analysis with missing data. The background image can be estimated for each frame. Finally, a simple background subtraction can segment the foreground. The effectiveness of our method is demonstrated in different illumination conditions and compared to the commonly used Gaussian mixture models method.

Keywords:
Background subtraction Artificial intelligence Computer vision Computer science Frame (networking) Motion estimation Image subtraction Motion analysis Image (mathematics) Mixture model Image processing Pattern recognition (psychology) Pixel Binary image

Metrics

2
Cited By
0.31
FWCI (Field Weighted Citation Impact)
18
Refs
0.64
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Video Surveillance and Tracking Methods
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Vision and Imaging
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image Processing Techniques and Applications
Physical Sciences →  Engineering →  Media Technology

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