Video browser showdown by NUS

Please use this identifier to cite or link to this item: https://doi.org/10.1007/978-3-642-27355-1_64

Title:	Video browser showdown by NUS
Authors:	Yuan, J. Luan, H. Hou, D. Zhang, H. Zheng, Y.-T. Zha, Z.-J. Chua, T.-S.
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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