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|Title:||Video browser showdown by NUS||Authors:||Yuan, J.
|Issue Date:||2012||Citation:||Yuan, J.,Luan, H.,Hou, D.,Zhang, H.,Zheng, Y.-T.,Zha, Z.-J.,Chua, T.-S. (2012). Video browser showdown by NUS. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 7131 LNCS : 642-645. ScholarBank@NUS Repository. https://doi.org/10.1007/978-3-642-27355-1_64||Abstract:||The known item search task (KIS) aims to retrieve a unique video or video clip in the video corpus. This paper presents a novel interactive video browsing system for KIS task. Our system integrates visual content-based, text-based and concept-based search approaches. It allows users to flexibly choose the search approaches. Moreover, two novel feedback schemes are employed: first, users can specify the temporal order in visual and conceptual inputs; second, users can label related samples with respect to visual, textual and conceptual features. Adopting these two feedback schemes greatly enhances search performance. © 2012 Springer-Verlag.||Source Title:||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)||URI:||http://scholarbank.nus.edu.sg/handle/10635/40873||ISBN:||9783642273544||ISSN:||03029743||DOI:||10.1007/978-3-642-27355-1_64|
|Appears in Collections:||Staff Publications|
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