Title :
On the study of moving objects detection and pattern recognition using LS-SVM
Author :
Ge, Guangying ; Tian, Cunwei ; Wang, Minggong
Author_Institution :
Liaocheng Univ., Liaocheng
Abstract :
Based on pattern recognition theory and support vector machine(SVM) technology, moving objects automatic detection, recognition and classification method are discussed in detail. An algorithm of moving objects detection on the combination of double inter-frame difference dasiaorpsila operating and a new multi-sorts classification method-binary exponent classification are presented. By comparing SVM with BP neural network in vehicle classification, Experimental results showed that SVM algorithm improve recognition rate and the can recognize and classify moving objects rapidly and effectively.
Keywords :
backpropagation; image classification; neural nets; object detection; support vector machines; BP neural network; LS-SVM; binary exponent classification; classification method; double inter-frame difference; object detection; pattern recognition; support vector machine; Automation; Electronic mail; Intelligent control; Least squares methods; Neural networks; Object detection; Pattern recognition; Support vector machine classification; Support vector machines; Vehicles; Least Squares Support Vector Machine(LS-SVM); moving objects classification; moving objects detection; pattern recognition;
Conference_Titel :
Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4244-2113-8
Electronic_ISBN :
978-1-4244-2114-5
DOI :
10.1109/WCICA.2008.4593314
