Motion Flow Segmentation Based on Optical Flow Angle
Kun Yang, Lin Wang, Fu-Jian Feng, Jiang-Hao Yu, Yuan-Fei Cheng
Available Online December 2016.
- https://doi.org/10.2991/icwcsn-16.2017.120How to use a DOI?
- Optical flow; Lyapunov exponent; Crowd target detection; Motion flow segmentation.
- Aiming at the irrationality of deep motion state analysis, such as density estimation, target tracking and behavior understanding, which taken the motion foreground as a whole in dense crowd scene. This paper proposes an algorithm to segment motion flow based on optical flow angle. First of all, the motion prospect is obtained by using the finite-time Lyapunov exponent (FTLE) algorithm. Then get the foreground optical flow information with the prospect as a mask. Finally, the dynamic K-means clustering method is applied to segment the foreground optical flow angle. Experimental results show that the proposed algorithm is clear and easy to implement, and the motion flow can be segmented accurately in different scenes.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Kun Yang AU - Lin Wang AU - Fu-Jian Feng AU - Jiang-Hao Yu AU - Yuan-Fei Cheng PY - 2016/12 DA - 2016/12 TI - Motion Flow Segmentation Based on Optical Flow Angle BT - 3rd International Conference on Wireless Communication and Sensor Networks (WCSN 2016) PB - Atlantis Press SN - 2352-538X UR - https://doi.org/10.2991/icwcsn-16.2017.120 DO - https://doi.org/10.2991/icwcsn-16.2017.120 ID - Yang2016/12 ER -