Imaging Components, Systems, and Processing

Far-infrared pedestrian detection for advanced driver assistance systems using scene context

[+] Author Affiliations
Guohua Wang, Qiong Liu, Qingyao Wu

South China University of Technology, School of Software Engineering, No. 382 Waihuan East Road, Guangzhou 510006, China

Opt. Eng. 55(4), 043105 (Apr 21, 2016). doi:10.1117/1.OE.55.4.043105
History: Received September 9, 2015; Accepted March 30, 2016
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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.

© 2016 Society of Photo-Optical Instrumentation Engineers

Citation

Guohua Wang ; Qiong Liu and Qingyao Wu
"Far-infrared pedestrian detection for advanced driver assistance systems using scene context", Opt. Eng. 55(4), 043105 (Apr 21, 2016). ; http://dx.doi.org/10.1117/1.OE.55.4.043105


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