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.
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CITATION STYLE
Yuan, J., Luan, H., Hou, D., Zhang, H., Zheng, Y. T., Zha, Z. J., & Chua, T. S. (2012). Video browser showdown by NUS. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7131 LNCS, pp. 642–645). https://doi.org/10.1007/978-3-642-27355-1_64
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