NDLI: A fast pedestrian detection via modified HOG feature

Content Provider	IEEE Xplore Digital Library
Author	Li Weixing Su Haijun Pan Feng Gao Qi Quan Bin
Copyright Year	2015
Description	Author affiliation: Sch. of Autom., Beijing Inst. of Technol., Beijing, China (Li Weixing; Su Haijun; Pan Feng; Gao Qi; Quan Bin)
Abstract	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.
Starting Page	3870
Ending Page	3873
File Size	358607
Page Count	4
File Format	PDF
ISBN	9789881563897
ISSN	19341768
DOI	10.1109/ChiCC.2015.7260236
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-07-28
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Technical Committee on Control Theory, Chinese Association of Automation
Subject Keyword	Support vector machines Histograms Computer vision Accuracy Error analysis Conferences Feature extraction SVM Pedestrian Detection Combination of HOG Channels
Content Type	Text
Resource Type	Article

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