%0 Journal Article %1 WANG201771 %A Wang, Heng %A Wang, Bin %A Liu, Bingbing %A Meng, Xiaoli %A Yang, Guanghong %D 2017 %J Robotics and Autonomous Systems %K lidar ml order1 pedestrian %P 71 - 78 %R https://doi.org/10.1016/j.robot.2016.11.014 %T Pedestrian recognition and tracking using 3D LiDAR for autonomous vehicle %U http://www.sciencedirect.com/science/article/pii/S0921889015302633 %V 88 %X This paper studies the pedestrian recognition and tracking problem for autonomous vehicles using a 3D LiDAR, a classifier trained by SVM (Support Vector Machine) is used to recognize pedestrians, the recognition performance is further improved with the aid of tracking results. By comparing positions and velocity directions of pedestrians with curb information, alarms will be generated if pedestrians are detected to be on road or close to curbs. The proposed approach has been verified on an autonomous vehicle platform.

@article{WANG201771, abstract = {This paper studies the pedestrian recognition and tracking problem for autonomous vehicles using a 3D LiDAR, a classifier trained by SVM (Support Vector Machine) is used to recognize pedestrians, the recognition performance is further improved with the aid of tracking results. By comparing positions and velocity directions of pedestrians with curb information, alarms will be generated if pedestrians are detected to be on road or close to curbs. The proposed approach has been verified on an autonomous vehicle platform.}, added-at = {2020-05-27T22:44:32.000+0200}, author = {Wang, Heng and Wang, Bin and Liu, Bingbing and Meng, Xiaoli and Yang, Guanghong}, biburl = {https://www.bibsonomy.org/bibtex/2a416a5ab9fed3fec48f34bc26f6bdb1c/sohnki}, description = {Pedestrian recognition and tracking using 3D LiDAR for autonomous vehicle - ScienceDirect}, doi = {https://doi.org/10.1016/j.robot.2016.11.014}, interhash = {e53cb9091f99f7b5613b6341f4d16897}, intrahash = {a416a5ab9fed3fec48f34bc26f6bdb1c}, issn = {0921-8890}, journal = {Robotics and Autonomous Systems}, keywords = {lidar ml order1 pedestrian}, pages = {71 - 78}, timestamp = {2020-06-02T20:02:37.000+0200}, title = {Pedestrian recognition and tracking using 3D LiDAR for autonomous vehicle}, url = {http://www.sciencedirect.com/science/article/pii/S0921889015302633}, volume = 88, year = 2017 }