Pedestrian recognition and tracking using 3D LiDAR for autonomous vehicle

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• 作者：Heng Wang^a ; ^b ; ^{wangheng@mail.neu.edu.cn}Author Vitae ; Bin Wang^b ; ^{wangb@i2r.a-star.edu.sg}Author Vitae ; Bingbing Liu^b ; ^{bliu@i2r.a-star.edu.sg}Author Vitae ; Xiaoli Meng^b ; ^{mangx@i2r.a-star.edu.sg}Author Vitae ; Guanghong Yang^a ; ^{yangguanghong@mail.neu.edu.cn}Author Vitae
• 关键词：Pedestrian recognition and tracking ; Point clouds ; Hash table ; GUI design
• 刊名：Robotics and Autonomous Systems
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：88
• 期：Complete
• 页码：71-78
• 全文大小：3642 K
• 卷排序：88

文摘

Curb information is used to divide pedestrian candidates into two classes, i.e., on-road and out of road. Tracking aided recognition strategy is used to improve the true positive rate, for example, for those on-road candidates, who have been recognized as pedestrians in former frame are classified to be pedestrians directly. This may increase the true positive rate for candidates who become too close or too far from moving autonomous vehicle in the following frames, where only a few laser beams are irradiated on pedestrians. Hash table is used for searching and comparison in the segmentation procedure to increase the efficiency of the proposed algorithm. The pedestrian recognition and tracking system is integrated with the autonomous vehicle platform which provides timely prediction of pedestrian motions.