Traffic accident prediction using 3-D model-based vehicle tracking
文献类型：专利
| 作者 | Hu, WM ; Xiao, XJ; Xie, D; Tan, TN; Maybank, S
|
| 发表日期 | 2004-05-01 |
| 关键词 | activity patterns prediction of traffic accidents three-dimensional (3-D) model-based vehicle tracking |
| 英文摘要 | Intelligent visual surveillance for road vehicles is the key to developing autonomous intelligent traffic systems. Recently, traffic incident detection employing computer vision and image processing has attracted much attention. In this paper, a probabilistic model for predicting traffic accidents using three-dimensional (3-D) model-based vehicle tracking is proposed. Sample data including motion trajectories are first obtained by 3-D model-based vehicle tracking. A fuzzy self-organizing neural network algorithm is then applied to learn activity patterns from the sample trajectories. Finally, vehicle activity is predicted by locating and matching each partial trajectory with the learned activity patterns, and the occurrence probability of a traffic accident is determined. Experiments show the effectiveness of the proposed algorithms. |
| 语种 | 英语 |
| WOS记录号 | WOS:000221517200012 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/7989]  |
| 专题 | 自动化研究所_09年以前成果 |
| 作者单位 | 1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100080, Peoples R China 2.Univ London Birkbeck Coll, Sch Comp Sci & Informat Syst, London WC1E 7HX, England |
| 推荐引用方式 GB/T 7714 | Hu, WM,Xiao, XJ,Xie, D,et al. Traffic accident prediction using 3-D model-based vehicle tracking. 2004-05-01. |
入库方式： OAI收割
来源：自动化研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。