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CBVIR approach to video-based surveillance is discussed. The objective is to detect in real time near-duplicates (e.g. similarly-looking objects) simultaneously appearing in concurrently captured/played videos. A novel method of keypoint matching is proposed, based on keypoint descriptions additionally incorporating visual and geometric contexts. Near-duplicate fragments can be identified by keypoint matching only. The analysis of geometric constraints (a bottleneck of typical CBVIR methods for sub-image retrieval) is not required. When the proposed method is fully implemented, high-speed and good performances can be achieved, as preliminarily shown in proof-of-concept experiments. The method is affine-invariant and employs typical keypoint detectors and descriptors (MSER and SIFT) as the low-level mechanisms.

Near-duplicate Fragments in Simultaneously Captured Videos - A Study on Real-time Detection using CBVIR Approach