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このアイテムの引用には次の識別子を使用してください: http://hdl.handle.net/10119/15256

タイトル: Informative Sequential Patch Selection for Image Retrieval
著者: Shen, Zhihao
Jeong, Sungmoon
Lee, Hosun
Chong, Nak Young
キーワード: Image retrieval
sequential feature selection
field of view
visual attention
発行日: 2017-07-18
出版者: Institute of Electrical and Electronics Engineers (IEEE)
誌名: 2017 IEEE International Conference on Information and Automation (ICIA)
開始ページ: 213
終了ページ: 218
DOI: 10.1109/ICInfA.2017.8078908
抄録: To quickly and efficiently analyze a large-scale environment by the camera with limited field-of-view, intelligent systems should sequentially select the optimal field-of-view to observe important and informative parts of area. Especially in the image retrieval tasks, small observations could be sequentially selected to improve the performance of image retrieval with less computational costs than whole observations at once and the enhanced retrieval performance could be used to select the next best-view again in a cyclic process. In this paper, we have investigated the effects of selected image patches, which might be either overlapped with a certain ratio or non-overlapped with previous observations, in this cyclic process. The adaptive patch selection algorithm is also described as follows: (1) A current observation is decided by its own information gain model which is designed by a similarity value between current observed information and training dataset. (2) After then, the system will update the information gain model by discarding the irrelevant training data with the current observation. During this process, we have shown that an informative patch, even though a part of selected patch is already observed at previous steps, can enhance the retrieval accuracy and it has a better performance than an independent observation method. Experimental results also have shown that the model selects the informative patches around the important contents to retrieve the target images such as the sky, building and so on.
Rights: This is the author's version of the work. Copyright (C) 2017 IEEE. 2017 IEEE International Conference on Information and Automation (ICIA), 2017, 213-218. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
URI: http://hdl.handle.net/10119/15256
資料タイプ: author
出現コレクション:b11-1. 会議発表論文・発表資料 (Conference Papers)

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