Far-Infrared Based Pedestrian Detection for Driver-Assistance Systems Based on Candidate Filters, Gradient-Based Feature and Multi-Frame Approval Matching

Sensors

Guohua Wang²  Qiong Liu¹ 

[1] School of Software Engineering, South China University of Technology, No. 382 Waihuan East Rd., Guangzhou 510006, China

关键词: pedestrian detection;    far-infrared video;    advanced driver-assistance systems;    gradient-based feature;    candidate filters;   

DOI  :  10.3390/s151229874

来源: mdpi

【 摘 要 】

Far-infrared pedestrian detection approaches for advanced driver-assistance systems based on high-dimensional features fail to simultaneously achieve robust and real-time detection. We propose a robust and real-time pedestrian detection system characterized by novel candidate filters, novel pedestrian features and multi-frame approval matching in a coarse-to-fine fashion. Firstly, we design two filters based on the pedestrians’ head and the road to select the candidates after applying a pedestrian segmentation algorithm to reduce false alarms. Secondly, we propose a novel feature encapsulating both the relationship of oriented gradient distribution and the code of oriented gradient to deal with the enormous variance in pedestrians’ size and appearance. Thirdly, we introduce a multi-frame approval matching approach utilizing the spatiotemporal continuity of pedestrians to increase the detection rate. Large-scale experiments indicate that the system works in real time and the accuracy has improved about 9% compared with approaches based on high-dimensional features only.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.