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