Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.ins.2012.01.003
Title: K-Partite graph reinforcement and its application in multimedia information retrieval
Authors: Gao, Y.
Wang, M.
Ji, R.
Zha, Z. 
Shen, J.
Keywords: 3D object retrieval
k-Partite graph reinforcement
Multimedia information retrieval
Video retrieval
Issue Date: 2012
Source: Gao, Y., Wang, M., Ji, R., Zha, Z., Shen, J. (2012). K-Partite graph reinforcement and its application in multimedia information retrieval. Information Sciences 194 : 224-239. ScholarBank@NUS Repository. https://doi.org/10.1016/j.ins.2012.01.003
Abstract: In many example-based information retrieval tasks, example query actually contains multiple sub-queries. For example, in 3D object retrieval, the query is an object described by multiple views. In content-based video retrieval, the query is a video clip that contains multiple frames. Without prior knowledge, the most intuitive approach is to treat the sub-queries equally without difference. In this paper, we propose a k-partite graph reinforcement approach to fuse these sub-queries based on the to-be-retrieved database. The approach first collects the top retrieved results. These results are regarded as pseudo-relevant samples and then a k-partite graph reinforcement is performed on these samples and the query. In the reinforcement process, the weights of the sub-queries are updated by an iterative process. We present experiments on 3D object retrieval and content-based video clip retrieval, and the results demonstrate that our method effectively boosts retrieval performance. © 2012 Elsevier Inc. All rights reserved.
Source Title: Information Sciences
URI: http://scholarbank.nus.edu.sg/handle/10635/39137
ISSN: 00200255
DOI: 10.1016/j.ins.2012.01.003
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