| 標題: | Multiple target tracking in occlusion area with interacting object models in urban environments |
| 作者: | Chen, Jiun-Fu Wang, Chieh-Chih Chou, Cheng-Fu 資訊工程學系 Department of Computer Science |
| 關鍵字: | Multitarget tracking;Interaction;LIDAR |
| 公開日期: | 1-May-2018 |
| 摘要: | Multiple target tracking in crowded urban environments is a daunting task. High crowdedness complicates motion modeling, and occlusion makes tracking difficult as well. Based on the variable-structure multiple -model (VSMM) estimation framework, this paper extends an interacting object tracking (IOT) scheme with occlusion detection and a virtual measurement model for occluded areas. IOT is composed of a scene interaction model and a neighboring object interaction model. The scene interaction model considers the long-term interactions of a moving object and surroundings, and the neighboring object interaction model considers three short-term interactions. With these interacting object models, the motion feature of a moving object can be represented with the weight of each model. A virtual measurement model is proposed to exploit the motion feature with the IOT scheme under occlusion. The proposed approach was validated using a stationary 2D LIDAR. To verify in occlusion, a 3D LIDAR based benchmark system was developed to extract occluded moving segments. The ample experimental results show that the proposed IOT scheme tracks over 57% of occluded moving objects in an urban intersection. (C) 2018 Elsevier B.V. All rights reserved. |
| URI: | http://dx.doi.org/10.1016/j.robot.2018.02.004 http://hdl.handle.net/11536/144904 |
| ISSN: | 0921-8890 |
| DOI: | 10.1016/j.robot.2018.02.004 |
| 期刊: | ROBOTICS AND AUTONOMOUS SYSTEMS |
| Volume: | 103 |
| 起始頁: | 68 |
| 結束頁: | 82 |
| Appears in Collections: | Articles |

