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Proceedings Paper

Approach to part using deformable part model in pedestrian detection system
Author(s): Hye Ji Choi; Nara Shin; Kwang Nam Choi
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Paper Abstract

Histogram of Oriented Gradient (HOG) proposed by Dalal and Triggs is currently the most basic algorithm to detection pedestrian. The algorithm is weak to occlusion, since the algorithm trained by the image of pedestrian full body images as one feature. As a result, the detection rate using HOG feature becomes decreases remarkably. To solve this problem, the paper proposed detection system using Deformable Part-based Model (DPM) just divided two parts of pedestrian data through latent Support Vector Machine (SVM) based machine learning. Experimental results show that proposed approach achieves better performance on detection with high accuracy than existed method [1].

Paper Details

Date Published: 11 July 2016
PDF: 4 pages
Proc. SPIE 10011, First International Workshop on Pattern Recognition, 1001108 (11 July 2016); doi: 10.1117/12.2242984
Show Author Affiliations
Hye Ji Choi, Chung-Ang Univ. (Korea, Republic of)
Nara Shin, KSI Inc. (Korea, Republic of)
Kwang Nam Choi, Chung-Ang Univ. (Korea, Republic of)

Published in SPIE Proceedings Vol. 10011:
First International Workshop on Pattern Recognition
Xudong Jiang; Guojian Chen; Genci Capi; Chiharu Ishll, Editor(s)

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