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Title: Concept-based near-duplicate video clip detection for novelty re-ranking of web video search results
Authors: Bhatt, C.A.
Atrey, P.K.
Kankanhalli, M.S. 
Keywords: Concept-based near duplicates
Conceptual clustering of videos
Multimedia data mining
Near-duplicate video clip detection
Semantic novelty and redundancy detection
Video semantic time-series representation
Issue Date: 2012
Citation: Bhatt, C.A., Atrey, P.K., Kankanhalli, M.S. (2012). Concept-based near-duplicate video clip detection for novelty re-ranking of web video search results. Multimedia Systems 18 (4) : 337-358. ScholarBank@NUS Repository.
Abstract: State-of-the-art near-duplicate video clip (NDVC) detection for novelty re-ranking uses nonsemantic low-level features (color/texture) to detect and eliminate "content-based NDVC" and increases content level novelty in the top results. However, humans may perceive a video as near duplicate from a semantic perspective as well. In this paper, we propose concept-based near-duplicate video clip (CBNDVC) detection technique for novelty re-ranking. We identify "semantic NDVC", making use of the semantic features (events/concepts) and re-rank the top results to increase the content as well as semantic novelty. Videos are represented as a multivariate time series of confidence values of relevant concepts and thereafter discovery of CBNDVC clusters is achieved by conceptual clustering. Obtained results show higher precision and recall from the user's perspective. © Springer-Verlag 2011.
Source Title: Multimedia Systems
ISSN: 09424962
DOI: 10.1007/s00530-011-0253-x
Appears in Collections:Staff Publications

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