DocumentCode :
3467802
Title :
Human detection based on integral Histograms of Oriented Gradients and SVM
Author :
Said, Yahia ; Atri, Mohamed ; Tourki, Rached
Author_Institution :
Lab. of Electron. & Microelectron., Fac. of Sci. Monastir, Monastir, Tunisia
fYear :
2011
fDate :
3-5 March 2011
Firstpage :
1
Lastpage :
5
Abstract :
This paper presents a method for human detection in video sequence. The Histogram of Oriented Gradients (HOG) descriptors show experimentally significantly out-performs existing feature sets for human detection. Because of HOG computation influence on performance, we finally choose a more better HOG descriptor to extract human feature from visible spectrum images based on OpenCv and MS VC++. We realized an image descriptor based on Integral Histograms of Oriented Gradients (HOG), associated with a Support Vector Machine (SVM) classifier and evaluate its efficiency.
Keywords :
feature extraction; image classification; image sequences; object detection; support vector machines; video signal processing; MS VC++; OpenCv; SVM; histogram of oriented gradients descriptor; human detection; human feature extraction; image descriptor; integral histograms of oriented gradients; support vector machine classifier; video sequence; visible spectrum images; Computational efficiency; Computers; Degradation; Humans; Polynomials; Human detection; Image descriptor; Integral HoG; OpenCv; SVM;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Communications, Computing and Control Applications (CCCA), 2011 International Conference on
Conference_Location :
Hammamet
Print_ISBN :
978-1-4244-9795-9
Type :
conf
DOI :
10.1109/CCCA.2011.6031422
Filename :
6031422
Link To Document :
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