Surveillance based crowd counting via convolutional neural networks
文献类型：会议论文
| 作者 | Zhang, Damin1; Li, Zhanming1; Liu, Pengcheng2
|
| 出版日期 | 2016 |
| 会议日期 | October 19, 2016 - October 19, 2016 |
| 会议地点 | Beijing, China |
| DOI | 10.1007/978-981-10-3476-3_17 |
| 页码 | 140-146 |
| 通讯作者 | Liu, Pengcheng (liupengcheng@cigit.ac.cn) |
| 英文摘要 | Video surveillance based crowd counting is important for crowd management and public security. It is a challenge task due to the cluttered background, ambiguous foreground and diverse crowd distributions. In this paper, we propose an end-to-end crowd counting method with convolutional neural networks, which integrates original frames and motion cues for learning a deep crowd counting regressor. The original frames and motion cues are complementary to each other for counting the stationary and moving pedestrians. Experimental results on two widely-used crowd counting datasets demonstrate the effectiveness of our method, and achieve the state-of-the-art performance. © Springer Nature Singapore Pte Ltd. 2016. |
| 会议录 | 4th Chinese Conference on Intelligent Visual Surveillance, IVS 2016
 |
| 语种 | 英语 |
| ISSN号 | 18650929 |
| 源URL | [http://119.78.100.138/handle/2HOD01W0/4675]  |
| 专题 | 智能安全技术研究中心 |
| 作者单位 | 1.College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou, China; 2.Intelligent Media Technique Research Center, Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing, China |
| 推荐引用方式 GB/T 7714 | Zhang, Damin,Li, Zhanming,Liu, Pengcheng. Surveillance based crowd counting via convolutional neural networks[C]. 见:. Beijing, China. October 19, 2016 - October 19, 2016. |
入库方式： OAI收割
来源：重庆绿色智能技术研究院
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