Computing Optical Flow with Physical Models of Brightness Variation

Although most optical flow techniques presume brightness constancy, it is well-known that this constraint is often violated, producing poor estimates of image motion. This paper describes a generalized formulation of optical flow estimation based on models of brightness variations that are caused by time-dependent physical processes. These include changing surface orientation with respect to a directional illuminant, motion of the illuminant, and physical models of heat transport in infrared images. With these models, we simultaneously estimate the 2D image motion and the relevant physical parameters of the brightness change model. The estimation problem is formulated using total least squares, with confidence bounds on the parameters. Experiments in four domains, with both synthetic and natural inputs, show how this formulation produces superior estimates of the 2D image motion.