People counting using combined feature
文献类型：会议论文
| 作者 | Congwen Gao; Kaiqi Huang ; Tieniu Tan
|
| 出版日期 | 2011 |
| 会议日期 | 2011 |
| 会议地点 | Beijing, China |
| 关键词 | Statistical Analysis video Surveillance combined Feature |
| 页码 | 81–84 |
| 英文摘要 | In this paper, we present a new people counting approach in visual surveillance scenes. The features adopted in previous methods are all extracted at pixel-level or based on local area, which are severely affected by factors such as occlusion. To cover the shortage, we introduce a new feature which describes a people crowd as a whole. Because pedestrian behaviors change when the degree of crowdedness varies, we can capture motion information to model a crowd and characterize the pedestrian behaviors based on statistic analysis. Afterwards we combine together the two kinds of features presented above as the final people counting feature. Experiments conducted in real world scenes demonstrate the superior effectiveness of the proposed method. |
| 会议录 | Conference on Intelligent Visual Surveillance, 2011
 |
| 语种 | 英语 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/12698]  |
| 专题 | 自动化研究所_智能感知与计算研究中心 |
| 通讯作者 | Kaiqi Huang |
| 作者单位 | 中国科学院自动化研究所 |
| 推荐引用方式 GB/T 7714 | Congwen Gao,Kaiqi Huang,Tieniu Tan. People counting using combined feature[C]. 见:. Beijing, China. 2011. |
入库方式： OAI收割
来源：自动化研究所
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