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Pedestrian Detection Algorithm Based on Local Color Parallel Similarity Features Cover

Pedestrian Detection Algorithm Based on Local Color Parallel Similarity Features

By: Xianxian Tian,  Hong Bao,  Cheng Xu and  Bobo Wang  
Open Access
|Dec 2013

Abstract

HOG Feature is the mainstream feature applied in the field of pedestrian detection .HOG combined with CSS has good effects on pedestrian detection. Because of the large amount calculation of HOG and CSS, HOG and CSS has poor real-time performance, we propose LCSSF (Local Color Self Similarity Feature) avoiding calculating the global color similarity distribution of CSS. The tested results of the Inria and the street pedestrian database show that the accuracy of the HOG with LCSSF has better detection performance and better real-time performance than HOG and CSS.

Language: English
Page range: 1869 - 1890
Submitted on: Jul 1, 2013
Accepted on: Oct 30, 2013
Published on: Dec 16, 2013
Published by: Professor Subhas Chandra Mukhopadhyay
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2013 Xianxian Tian, Hong Bao, Cheng Xu, Bobo Wang, published by Professor Subhas Chandra Mukhopadhyay
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.