Pedestrian Detection by Fusing 3D Points and Color Images

DOI

10.2991/ijndc.2016.4.4.6How to use a DOI?

Keywords

pedestrian detection; data fusion; LIDAR; histograms of oriented gradients (HOG); multi-sensor system

Abstract

In this paper, a fusing approach of a 3D sensor and a camera are used to improve the reliability of pedestrian detection. The proposed pedestrian detecting system adopts DBSCAN to cluster 3D points and projects the candidate clusters onto images as region of interest (ROI). Those ROIs are detected by HOG (histograms of oriented gradients) pedestrian detector. Because the DBSCAN groups together 3D points and rejects outlier points correctly, the proposed system has a low false detection rate. The performance is also improved since the proposed system only detects the ROI instead of the whole color image.

Copyright

© 2017, 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  - JOUR
AU  - Ben-Zhong Lin
AU  - Chien-Chou Lin
PY  - 2016
DA  - 2016/10/03
TI  - Pedestrian Detection by Fusing 3D Points and Color Images
JO  - International Journal of Networked and Distributed Computing
SP  - 252
EP  - 257
VL  - 4
IS  - 4
SN  - 2211-7946
UR  - https://doi.org/10.2991/ijndc.2016.4.4.6
DO  - 10.2991/ijndc.2016.4.4.6
ID  - Lin2016
ER  -