Abstract

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.

Keywords

Optical flowMotion fieldComputer visionComputer scienceArtificial intelligenceMotion estimationImage planeComputationProjection (relational algebra)Structure from motionFlow (mathematics)Motion (physics)Image (mathematics)GeometryAlgorithmMathematics

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Publication Info

Year
1995
Type
review
Volume
27
Issue
3
Pages
433-466
Citations
1236
Access
Closed

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Steven S. Beauchemin, John A. Barron (1995). The computation of optical flow. ACM Computing Surveys , 27 (3) , 433-466. https://doi.org/10.1145/212094.212141

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DOI
10.1145/212094.212141