A New Method for Computing Optical Flow

Accurate and high density estimation of optical flow vectors in an image sequence is accomplished by a method that estimates the velocity distribution function for small overlapping regions of the image. Because the distribution is multimodal, the method can accurately estimate the change in velocity near motion contrast borders. Large spatiotemporal support without sacrificing spatial resolution is a feature of the method, so it is not necessary to smooth the resulting flow vectors in a subsequent operation, and there is a certain degree of resistance to aperture and aliasing effects. Spatial support also provides for the accurate estimation of long-range displacements, and subpixel accuracy is achieved by a simple maximum likelihood estimation of the velocity distribution function. A confidence value is also estimated, which can help to predict flow ambiguities. The method is demonstrated using image sequences obtained from the analysis of ceramic and metal materials under stress.

• Type: Conference
• Year: 2000
• Where: BMVC
• Authors: W. F. Clocksin
• Keywords: BMVC 2000, Computer Vision, Flow Vectors, Image Sequences, Velocity Distribution Function