DocumentCode :
2224898
Title :
Robust moving object region extraction using a column and row projection algorithm
Author :
Liu, Yang ; Li, Yi-Bo
Author_Institution :
Coll. of Autom. Eng., Nanjing Univ. of Aeronaut. Astronaut., Nanjing, China
Volume :
6
fYear :
2010
fDate :
20-22 Aug. 2010
Abstract :
In intelligent surveillance field, the numerous methods have been proposed for foreground extraction from a stationary or dynamic background from a general video sequence. It is very difficult for the proposed methods to have both high accuracy, low computational complexity and less memory requirements. Unlike previous approaches to object detection which detect objects by building adaptive models of the background, this paper discusses projecting the pixels in the observed image to the bottom row or the last column and using the change of projection to find the moving object region. The algorithm is easy to be realized and the computational complexity is very low. As one of methods for moving object detection, it has high efficiency firstly. Additionally, because the special characteristics of pixels is considered, it has a stronger ability to enhance the moving object region information in comparison with the congener methods. It is tested for various indoor and outdoor video sequences which reliably deals with illumination changes and other small motions.
Keywords :
computational complexity; feature extraction; image motion analysis; image sequences; object detection; video signal processing; video surveillance; column projection algorithm; computational complexity; foreground extraction; intelligent surveillance field; moving object detection; moving object region extraction; row projection algorithm; video sequence; Computational modeling; Motion segmentation; Tracking; Object region extraction; background subtraction; column projection; row projection;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Computer Theory and Engineering (ICACTE), 2010 3rd International Conference on
Conference_Location :
Chengdu
ISSN :
2154-7491
Print_ISBN :
978-1-4244-6539-2
Type :
conf
DOI :
10.1109/ICACTE.2010.5579402
Filename :
5579402
Link To Document :
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