View Independent Object Classification Based on Automated Ground Plane Rectification for Traffic Scene Surveillance
文献类型：会议论文
| 作者 | Zhaoxiang Zhang ; Min Li; Kaiqi Huang; Tieniu Tan
|
| 出版日期 | 2008-10-17 |
| 会议日期 | 17th October 2008 |
| 会议地点 | France |
| 关键词 | Traffic Scene Surveillance Object Feature Automated Ground Plane Rectification View Independent Object Classification Online Learning Framework |
| 页码 | 1-9 |
| 英文摘要 | We address the problem of view independent object classification. Our aim is to classify moving objects of traf- fic scene surveillance videos into pedestrians, bicycles and vehicles. However, this problem is very challenging due to large object appearance variance, low resolution videos and limited object size. Especially, perspective distortion of surveillance cameras makes most 2D object features like size and speed related to view angles and not suitable for object classification. In this paper, we adopt the common constraint that most objects of interest in traffic scenes are moving on the ground plane. Firstly, we realize the ground plane rectification based on appearance and motion information of moving objects, which can be applied for normalization of 2D object features. An online learning framework is then described to achieve automatic object classification based on rectified 2D object features. Experimental results demonstrate the effectiveness, efficiency and robustness of the proposed method. |
| 会议录 | IEEE Conference on Computer Vision & Pattern Recognition 2008
 |
| 语种 | 英语 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/12709]  |
| 专题 | 自动化研究所_智能感知与计算研究中心 |
| 通讯作者 | Zhaoxiang Zhang |
| 推荐引用方式 GB/T 7714 | Zhaoxiang Zhang,Min Li,Kaiqi Huang,et al. View Independent Object Classification Based on Automated Ground Plane Rectification for Traffic Scene Surveillance[C]. 见:. France. 17th October 2008. |
入库方式： OAI收割
来源：自动化研究所
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