Paper Info
Title
Background subtraction based on phase and distance transform under sudden illumination change
Abstract
Effective foreground detection under sudden illumination change is an active research topic. However, most existing background subtraction approaches, which are intensity based, fail to handle this situation. In this paper, we propose a novel background modeling method that overcomes this limitation by relying on statistical models which use pixel phase instead of intensities. We first extract the phase feature of the pixel using Gabor filters. Then, a phase based background subtraction approach is proposed. In this approach, each phase feature is modeled independently by a mixture of Gaussian models and updated with a novel scheme. Since foreground pixels are scattered in the preliminary detection result, distance transform is implemented on the binary image which transforms the image into a distance map. We segment the distance image with a threshold and get the final result. Experiments on two challenging sequences demonstrate the effectiveness and robustness of our method.
Year
DOI
Venue
2010
10.1109/ICIP.2010.5650111
ICIP
Keywords
Field
DocType
gabor filters,phase,background subtraction,phase transform,gabor filter,phase based background subtraction,feature extraction,distance transform,object detection,pixel phase,phase feature,background modeling method,sudden illumination change,statistical model,binary image,mixture of gaussians
Background subtraction,Object detection,Computer vision,Pattern recognition,Computer science,Binary image,Feature extraction,Foreground detection,Distance transform,Pixel,Artificial intelligence,Gabor transform
Conference
ISSN
ISBN
Citations 
1522-4880 E-ISBN : 978-1-4244-7993-1
978-1-4244-7993-1
5
PageRank 
References 
Authors
0.50
6
3
Name
Order
Citations
PageRank
Gengjian Xue1825.89
Jun Sun27611.28
Li Song332365.87