Telefonica Research at TRECVID 2010 Content-Based Copy Detection

This notebook paper presents the participation of Telefonica Research in the task of Video Copy Detection in TRECVID 2010. This is our second participation and, for this year, we have developed two local-based monomodal systems that we then combine using a score-based fusion to obtain a multimodal system output. We submitted 4 runs in total, whose main characteristics are described below: • TID.m.[BALANCED/NOFA].fusion: These correspond to our main submission, both for the no false alarm and balanced profiles. They are based on the fusion between the local audio and local video monomodal systems. • TID.m.BALANCED.videoonly: This submission is based on the monomodal video-based system using DART local features and with a temporal consistency postprocessing. • TID.m.BALANCED.audioonly: This submission is based on the monomodal audio-based system using frequency-based audio local features. From these four systems submitted, two of them are processing only monomodal information (audio or video) and the fusion system takes the output of the previous two to output a fused result. Results for the monomodal systems in terms of NDCR are far from optimal, mainly due to an exces of false alarms that our monomodal systems still output. Results for F1 scores are very good for all cases. When combining the monomodal systems into he fusion the NDCR scores improve quite a bit as most false alarms are eliminated. The proposed fusion turned out to work very well for combining our two monomodal systems. We will further investigate it to improve it for future evaluations.