Share Email Print

Optical Engineering

Far-infrared pedestrian detection for advanced driver assistance systems using scene context
Author(s): Guohua Wang; Qiong Liu; Qingyao Wu
Format Member Price Non-Member Price
PDF $20.00 $25.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Pedestrian detection is one of the most critical but challenging components in advanced driver assistance systems. Far-infrared (FIR) images are well-suited for pedestrian detection even in a dark environment. However, most current detection approaches just focus on pedestrian patterns themselves, where robust and real-time detection cannot be well achieved. We propose a fast FIR pedestrian detection approach, called MAP-HOGLBP-T, to explicitly exploit the scene context for the driver assistance system. In MAP-HOGLBP-T, three algorithms are developed to exploit the scene contextual information from roads, vehicles, and background objects of high homogeneity, and we employ the Bayesian approach to build a classifier learner which respects the scene contextual information. We also develop a multiframe approval scheme to enhance the detection performance based on spatiotemporal continuity of pedestrians. Our empirical study on real-world datasets has demonstrated the efficiency and effectiveness of the proposed method. The performance is shown to be better than that of state-of-the-art low-level feature-based approaches.

Paper Details

Date Published: 21 April 2016
PDF: 18 pages
Opt. Eng. 55(4) 043105 doi: 10.1117/1.OE.55.4.043105
Published in: Optical Engineering Volume 55, Issue 4
Show Author Affiliations
Guohua Wang, South China Univ. of Technology (China)
Qiong Liu, South China Univ. of Technology (China)
Qingyao Wu, South China Univ. of Technology (China)

© SPIE. Terms of Use
Back to Top