Department of Computer Science, University of Minnesota, Minneapolis, MN 55455.
IEEE Trans Pattern Anal Mach Intell. 1985 Apr;7(4):374-83. doi: 10.1109/tpami.1985.4767677.
Optical flow can be used to locate dynamic occlusion boundaries in an image sequence. We derive an edge detection algorithm sensitive to changes in flow fields likely to be associated with occlusion. The algorithm is patterned after the Marr-Hildreth zero-crossing detectors currently used to locate boundaries in scalar fields. Zero-crossing detectors are extended to identify changes in direction and/or magnitude in a vector-valued flow field. As a result, the detector works for flow boundaries generated due to the relative motion of two overlapping surfaces, as well as the simpler case of motion parallax due to a sensor moving through an otherwise stationary environment. We then show how the approach can be extended to identify which side of a dynamic occlusion boundary corresponds to the occluding surface. The fundamental principal involved is that at an occlusion boundary, the image of the surface boundary moves with the image of the occluding surface. Such information is important in interpreting dynamic scenes. Results are demonstrated on optical flow fields automatically computed from real image sequences.
光流可用于定位图像序列中的动态遮挡边界。我们推导出一种对可能与遮挡相关的流场变化敏感的边缘检测算法。该算法的模式是模仿当前用于在标量场中定位边界的 Marr-Hildreth 零交叉检测器。零交叉检测器扩展到识别向量值流场中方向和/或大小的变化。因此,该检测器适用于由于两个重叠表面的相对运动产生的流边界,以及由于传感器在静止环境中移动而产生的更简单的运动视差情况。然后,我们展示如何扩展该方法以识别动态遮挡边界的哪一侧对应于遮挡表面。所涉及的基本原理是,在遮挡边界处,表面边界的图像随遮挡表面的图像移动。此类信息对于解释动态场景很重要。结果在自动从真实图像序列计算的光流场上进行了演示。