DocumentCode :
557582
Title :
Multi-directional crowded objects segmentation based on optical flow histogram
Author :
Cui Shiyao ; Li Nianqiang ; Liu Zhen
Author_Institution :
Sch. of Inf. Sci. & Eng., Univ. of Jinan, Jinan, China
Volume :
1
fYear :
2011
fDate :
15-17 Oct. 2011
Firstpage :
552
Lastpage :
555
Abstract :
This paper proposes an adaptive crowded objects segment algorithm. First, a real time global optical flow method is employed to calculate velocity field and the background noise is eliminated by setting threshold. Second, the angle matrix of foreground optical flow is treated as gray scale image, and its histogram curve is segmented instead of optical flow foreground. Through the histogram derivative curve, a set of segment points is picked up, and then foreground area is segmented into different flows. During the segmentation, some small blocks appear. A block absorption approach is proposed to solve this problem, which makes use of the color characteristic of flows. Some experimental results show the algorithm is efficient. Compared to clustering methods, the proposed approach has similar segment result, but is very time saving. The approach is more suitable for real time applications.
Keywords :
image colour analysis; image motion analysis; image segmentation; image sequences; pattern clustering; adaptive crowded object segment algorithm; background noise elimination; block absorption approach; clustering methods; flow color characteristic; global optical flow method; gray scale image; histogram derivative curve; multidirectional crowded object segmentation; optical flow histogram; velocity field calculation; Absorption; Feature extraction; Histograms; Image color analysis; Image segmentation; Object segmentation; Optical imaging;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image and Signal Processing (CISP), 2011 4th International Congress on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-9304-3
Type :
conf
DOI :
10.1109/CISP.2011.6099914
Filename :
6099914
Link To Document :
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