A fast pedestrian detection via modified HOG feature

The Histogram of Oriented Gradient (HOG) feature for pedestrian detection has achieved good results, but it is time-consuming. For resolving this problem, a modified method for HOG is proposed to reduce the dimension of the features. On the base of analyzing the process of HOG, nine independent HOG...

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Bibliographic Details
Published in2015 34th Chinese Control Conference (CCC) pp. 3870 - 3873
Main Authors Weixing, Li, Haijun, Su, Feng, Pan, Qi, Gao, Bin, Quan
Format Conference Proceeding Journal Article
LanguageEnglish
Published Technical Committee on Control Theory, Chinese Association of Automation 01.07.2015
Subjects
Accuracy
Channels
Combination of HOG Channels
Computer vision
Conferences
Detection
Error analysis
Feature extraction
Histograms
Intervals
Orientation
Pedestrian Detection
Pedestrians
Regularity
Support vector machines
SVM
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Summary:The Histogram of Oriented Gradient (HOG) feature for pedestrian detection has achieved good results, but it is time-consuming. For resolving this problem, a modified method for HOG is proposed to reduce the dimension of the features. On the base of analyzing the process of HOG, nine independent HOG channels (HOG-C) are extracted according to the gradient orientation interval. Through evaluating the effectiveness of HOG-C for pedestrian detection individually, a combination of HOG channels (CHOG-C) feature is presented based on statistical regularities. Comprehensive experiments on INRIA database demonstrated the promising performance of the CHOG-C feature, and the experimental results shown that the dimension is reduced meanwhile without losing the accuracy.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Conference-1
ObjectType-Feature-3
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SourceType-Conference Papers & Proceedings-2
ISSN:1934-1768
DOI:10.1109/ChiCC.2015.7260236