2012 IEEE Conference on Computer Vision and Pattern Recognition (2012)
Providence, RI USA
June 16, 2012 to June 21, 2012
Li Zhang , Univ. of Wisconsin - Madison, Madison, WI, USA
T. Portz , Univ. of Wisconsin - Madison, Madison, WI, USA
Hongrui Jiang , Univ. of Wisconsin - Madison, Madison, WI, USA
This paper extends the classical warping-based optical flow method to achieve accurate flow in the presence of spatially-varying motion blur. Our idea is to parameterize the appearance of each frame as a function of both the pixel motion and the motion-induced blur. We search for the flows that best match two consecutive frames, which amounts to finding the derivative of a blurred frame with respect to both the motion and the blur, where the blur itself is a function of the motion. We propose an efficient technique to calculate the derivatives using prefiltering. Our technique avoids performing spatially-varying filtering (which can be computationally expensive) during the optimization iterations. In the end, our derivative calculation technique can be easily incorporated with classical flow code to handle video with non-uniform motion blur with little performance penalty. Our method is evaluated on both synthetic and real videos and outperforms conventional flow methods in the presence of motion blur.
optimisation, image motion analysis, image sequences, iterative methods, optimization iterations, spatially-varying motion blur, warping-based optical flow, pixel motion, motion-induced blur, spatially-varying filtering, Kernel, Optical imaging, Adaptive optics, Piecewise linear approximation, Measurement, Optical filters, Approximation methods
Li Zhang, T. Portz and Hongrui Jiang, "Optical flow in the presence of spatially-varying motion blur," 2012 IEEE Conference on Computer Vision and Pattern Recognition(CVPR), Providence, RI USA, 2012, pp. 1752-1759.