KMS Chongqing Institute of Green and Intelligent Technology, CAS
| Surveillance based crowd counting via convolutional neural networks | |
Zhang, Damin1; Li, Zhanming1; Liu, Pengcheng2
| |
| 2016 | |
| 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. |
| 语种 | 英语 |
| DOI | 10.1007/978-981-10-3476-3_17 |
| 会议(录)名称 | 4th Chinese Conference on Intelligent Visual Surveillance, IVS 2016
 |
| 页码 | 140-146 |
| 通讯作者 | Liu, Pengcheng (liupengcheng@cigit.ac.cn) |
| 收录类别 | EI |
| 会议地点 | Beijing, China |
| 会议日期 | October 19, 2016 - October 19, 2016 |
