Multiple feature hashing for real-time large scale near-duplicate video retrieval
MM '11 Proceedings of the 19th ACM international conference on Multimedia
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In this paper a particular issue is addressed: matching still images (screen shots) with videos. A content-based similarity search approach using image queries is proposed. A fast method based on local visual patterns both for matching and indexing is employed. But we argue that using every frames may limit the scalability of the approach. Therefore only keyframes are extracted and used. The main contribution of this paper is an investigation over the trade-off between accuracy and scalability using different keyframe rates for sampling the video database. This trade-off is evaluated on a ground truth using a large reference video database (1000 hours).