Fast Pedestrian Recognition Based on Multisensor Fusion

• Published in: Discrete Dynamics in Nature and Society Vol. 2012; no. 2012; pp. 881 - 894-063
• Main Authors: Hu, Hongyu, Qu, Zhaowei, Li, Zhihui, Hu, Jinhui, Wei, Fulu
• Format: Journal Article
• Language: English
• Published: Cairo, Egypt Hindawi Limiteds 01.01.2012; Hindawi Puplishing Corporation; Hindawi Publishing Corporation; Hindawi Limited
• Subjects: Algorithms; Cameras; Data processing; Feature extraction; Lasers; Multisensor fusion; Neural networks; Pedestrians; Processing speed; Real time; Recognition; Roads; Scanners; Sensors; Support vector machines; Traffic accidents & safety
• ISSN: 1026-0226; 1607-887X
• DOI: 10.1155/2012/318305

A fast pedestrian recognition algorithm based on multisensor fusion is presented in this paper. Firstly, potential pedestrian locations are estimated by laser radar scanning in the world coordinates, and then their corresponding candidate regions in the image are located by camera calibration and the perspective mapping model. For avoiding time consuming in the training and recognition process caused by large numbers of feature vector dimensions, region of interest-based integral histograms of oriented gradients (ROI-IHOG) feature extraction method is proposed later. A support vector machine (SVM) classifier is trained by a novel pedestrian sample dataset which adapt to the urban road environment for online recognition. Finally, we test the validity of the proposed approach with several video sequences from realistic urban road scenarios. Reliable and timewise performances are shown based on our multisensor fusing method.