Abstract
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.
Highlights
Pedestrians are vulnerable participants among all objects involved in the transportation system when crashes happen, especially those in motion under urban road scenarios 1
A support vector machine SVM classifier is trained by a novel pedestrian sample dataset which adapt to the urban road environment for online recognition
This paper aims to propose a real time pedestrian recognition algorithm based on laser scanner and vision information fusion
Summary
Pedestrians are vulnerable participants among all objects involved in the transportation system when crashes happen, especially those in motion under urban road scenarios 1. The current research is mainly focused on the application of visual sensors 4–6 , infrared IR imaging sensors 7, 8 , and radar sensors 9, to aware of pedestrians and obtain their safety state information for realizing active pedestrian protection. Depending on the complementarity information from different sensors, more reliable and robust pedestrian detection results could be obtained by processing multisource and heterogeneous data. In past two decades, reducing accidents involving vulnerable road users with fusion of different kinds of sensors has already been focused on by some research projects, such as APVRU , PAROTO 12 , PROTECTOR 13, 14 , and SAVE-U 15, in European countries. Scheunert et al detected range discontinuities utilized by laser scanner and high brightness region in the image by far infrared sensor FIR. Combining with a laser scanner and a camera, Broggi et al presented an application for detecting pedestrian appearing just behind occluding obstacles
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