Improved Pedestrian Detection Based on Extended Histogram of Oriented Gradients

DOI

10.2991/iccsee.2013.564How to use a DOI?

Keywords

histogram of oriented gradients, pedestrian detection,support vector machine, multi-scale detection

Abstract

In order to further improve pedestrian detection accuracy and avoid the disadvantage of original histogram of oriented gradients (HOG), differential template, overlap ratio and normalization method and so on are improved when HOG features are extracted, then more gradient information are extracted and feature description operators can be obtained which describe human detail features better in lager image regions or detection windows. Considering speed, we select support vector machine (SVM) using linear function kernel as a classifier. Multi-scale detection technique and non maxima suppression method are employed for precisely locating the pedestrians in the image. Experiments show that the human detection system improves detection accuracy and still maintains a relatively satisfactory speed.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Li-hong ZHANG
AU  - Lin LI
PY  - 2013/03
DA  - 2013/03
TI  - Improved Pedestrian Detection Based on Extended Histogram of Oriented Gradients
BT  - Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013)
PB  - Atlantis Press
SP  - 2250
EP  - 2253
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccsee.2013.564
DO  - 10.2991/iccsee.2013.564
ID  - ZHANG2013/03
ER  -