A color fingerprint of video shot for content identification

Abstract

In this paper we propose a novel space-time color feature representation for video shot and apply it to content identification. In this representation the shot is cut into k equal size segments, and each segment is represented by a blending image formed through averaging the pixels' values of each frame in this segment along time direction. Each blending image is then divided into equal size blocks, and two color patterns named major and minor colors among mean R,G,B are extracted for each block. Hence each shot can be represented by a fixed-length string. The experiment shows this representation is not only robust to image quality reduction, frame size and frame rate change, but also to color distortion such as brightness/contrast adjustment. We also give a video similarity measure based on this color feature to identify shot chunks. We conducted experiment on 100 video clips, and quite low error rates can be achieved when identifying small size shot chunks with significant color distortion. From the experiment we believe that this color feature is a compact and robust representation for video content, and effective for content identification.