Optical Flow Analysis Based on Spatio-Temporal Correlation of Dynamic Image

We propose several methods for analyzing the velocity of moving particles in dynamic images. The methods are based on the analysis of temporal mutual-correlation between the time series of gray level changes at a target pixel and that of its neighboring pixels on an image plane. In this paper, we clarify that the temporal mutual-correlation functions can be understood as the intersections of a kind of spatial autocorrelation of an image irradiance function which is assumed to be rigid. According to this new understanding and assuming a Gaussian-like decrease in the spatial autocorrelation, we clarify a relation between the correlation-value and the lag-time of the mutual-correlation and velocity of a moving object. This relation results in an improved method for determining the optical flow. Our previous methods are useful only for the analysis of spherical particle motion. However, the improved one can be applied to more general objects. From the analysis of the artificial image sequences, it is suggested that the accuracy of the obtained result is less than 0.01 ±0.01 p/f in speed and 1.0 ±2.0 deg in direction. These results indicate that the improved method has ten times the accuracy of the typical method called the “gradient method.” The improved method is also evaluated by analyzing an actual dynamic scene and confirmed to have the capability to measure the two-dimensional velocity field (i.e., optical flow).