Tuning Optical Flow Estimation with Image-driven Functions
This paper presents a variational model to com- compute the optical flow using image-driven functions. The inten- pute intensity, gradient and smoothness have different influences on each sity, image area. Thus, we propose the control functions that take the image as the input to tune the estimation process. We use the second moment matrix to characterize distinct image areas and embed these functions into the variational model. We also separate the gradient term and intensity term in the model. In addition, we use the coarse-to-fine strategy to deal with the large displacement in the image sequence. Experimental results show the stability of our proposed method on different image sequences.
Duc Dung Nguyen Jae Wook Jeon
Department of Electrical and Computer Engineering,Sungkyunkwan University,Korea
国际会议
2011 IEEE International Conference on Robotics and Automation(2011年IEEE世界机器人与自动化大会 ICRA 2011)
上海
英文
4840-4845
2011-05-09(万方平台首次上网日期,不代表论文的发表时间)