DocumentCode :
2662908
Title :
Tracking for moving object using invariant moment and particle filter
Author :
Taekyu, Yang ; Sukbum, Kang
Author_Institution :
Dept. of Intell. Robot Eng., Mokwon Univ., Daejoen
fYear :
2008
fDate :
16-18 July 2008
Firstpage :
351
Lastpage :
354
Abstract :
In this study we used invariant moments with particle filter to track the moving object effectively in video image which is inputted continuously. At first acquiring recursively the mean value and the variance of current each image pixel, then find background image according to above values. Second, subtract adaptively the current image from background image and detect the moving object by using vertical and horizontal histogram. Because the invariant moments is not so sensitive to various transforms such as translation, rotation and scale changes, we can robustly track the moving object by observing particle filter values based on Bayesian probability of pre-distribution and post-distribution. From some experiments, we demonstrate that invariant moment method with particle filter which is suggested above shows better tracking performances than the method of using particle filter only.
Keywords :
Bayes methods; image motion analysis; object detection; particle filtering (numerical methods); statistical distributions; tracking filters; video signal processing; Bayesian probability distribution; horizontal histogram; invariant moment; moving object tracking; particle filter; vertical histogram; video image; Electronic mail; Filtering; Humans; Intelligent robots; Moment methods; Object detection; Particle filters; Particle tracking; Pixel; Shape; Invariant Moment; Moving Object; Particle Filter; Tracking;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Conference, 2008. CCC 2008. 27th Chinese
Conference_Location :
Kunming
Print_ISBN :
978-7-900719-70-6
Electronic_ISBN :
978-7-900719-70-6
Type :
conf
DOI :
10.1109/CHICC.2008.4605325
Filename :
4605325
Link To Document :
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