IBM Research TRECVID-2010 Video Copy Detection and Multimedia Event Detection System

Abstract

In this paper, we describe the system jointly developed by IBM Research and Columbia University for video copy detection and multimedia event detection applied to the TRECVID-2010 video retrieval benchmark. A. Content-Based Copy Detection: The focus of our copy detection system this year was fusing three types of complementary fingerprints: a keyframe-based color correlogram, SIFTogram (bag of visual words), and a GIST-based fingerprint. However, in our official submissions, we did not use the color correlogram component since our best results on the training set came from the GIST and SIFTogram components. A summary of our runs is listed below: 1. IBM.m.nofa.gistG: A run based on the grayscale GIST frame-level feature, with at most 1 result per query, except in the case of ties. 2. IBM.m.balanced.gistG: As in the above run, but with including more results per query, though on average still less than 2. 3. IBM.m.nofa.gistGC: The result of the nofa.gistG run, fused with results from GIST features extracted from the R,G,B color channels. 4. IBM.m.nofa.gistGCsift: The result of the nofa.giestGC run, fused with a SIFTogram result.