光流
运动场
计算机视觉
计算机科学
人工智能
运动估计
像面
计算
投影(关系代数)
由运动产生的结构
流量(数学)
运动(物理)
图像(数学)
几何学
算法
数学
作者
Steven S. Beauchemin,John A. Barron
出处
期刊:ACM Computing Surveys
[Association for Computing Machinery]
日期:1995-09-01
卷期号:27 (3): 433-466
被引量:1114
标识
DOI:10.1145/212094.212141
摘要
Two-dimensional image motion is the projection of the three-dimensional motion of objects, relative to a visual sensor, onto its image plane. Sequences of time-orderedimages allow the estimation of projected two-dimensional image motion as either instantaneous image velocities or discrete image displacements. These are usually called the optical flow field or the image velocity field . Provided that optical flow is a reliable approximation to two-dimensional image motion, it may then be used to recover the three-dimensional motion of the visual sensor (to within a scale factor) and the three-dimensional surface structure (shape or relative depth) through assumptions concerning the structure of the optical flow field, the three-dimensional environment, and the motion of the sensor. Optical flow may also be used to perform motion detection, object segmentation, time-to-collision and focus of expansion calculations, motion compensated encoding, and stereo disparity measurement. We investigate the computation of optical flow in this survey: widely known methods for estimating optical flow are classified and examined by scrutinizing the hypothesis and assumptions they use. The survey concludes with a discussion of current research issues.
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