Video Dissolve and Wipe Detection via Spatio-Temporal Images of Chromatic Histogram Differences

Gradual transitions represent a challenging problem for temporal segmentation of video. Here we present two new features for detecting these. Recently, Ngo et al. set out a method for edge detection in spatio-temporal images made out of the central column (or row, or diagonal) of a video. A wipe generates a diagonal edge in such an image. In this paper we make use of all available pixels to generate spatio-temporal images. For each column of the frame (using only the DC values from a video MPEG), we form a 2D histogram based on chromaticity, and then intersect that histogram with that of the previous frame (one or several frames earlier). The result is an image in which cuts and wipes appear as very strong edges, almost 1’s in a background of zeroes. Dissolves require another approach; here we extend a color-distance based histogram metric due to Hafner et al. by applying the method to 2D Cb-Cr histograms and changing the definition so that the the metric displays a near-constant value during a dissolve, and zero elsewhere. We show results on videos that include fast subject motion and camera movements.