政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/37111

政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/37111

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政大機構典藏 > 資訊學院 > 資訊科學系 > 學位論文 > Item 140.119/37111

請使用永久網址來引用或連結此文件: https://nccur.lib.nccu.edu.tw/handle/140.119/37111

題名:	以眼動資訊增進基於內容的圖像檢索效能 Improving the Performance of Content Based Image Retrieval by Eye Tracking
作者:	張京文 Jhang ,Jing Wun
貢獻者:	陳良弼蔡介立 Chen, Arbee L.P. Tsai, Jie Li 張京文 Jhang ,Jing Wun
關鍵詞:	圖像檢索眼動軌跡眼動資訊 image retrieval eye tracking eye movement
日期:	2008
上傳時間:	2009-09-19 12:10:39 (UTC+8)
摘要:	在現今的基於內容的圖像檢索的研究中，會將人的主觀認知考慮進去。因為傳統的圖像檢索中採取低階特徵來找出圖片上可能的重要區域的方法和人的感覺還是有著相當大的語意上的鴻溝。然而藉由考慮人對圖片的主觀認知，可以讓人找到對它而言圖片上重要的部分，再去做圖像檢索，找出使用者想要的圖片。這樣的作法是比較自然且直觀的。還能達到個人化的效果，因為每個人對同一張圖片上覺得重要的物體可能不盡相同。在本論文中的圖像檢索系統採用眼動軌跡當作人的主觀認知來輔助檢索。因為在心理學的研究中有提到，人在看圖片的時候會有較多的凝視點落在他覺得重要的區域上。所以藉由這個理論，本論文利用使用者看圖片的眼動軌跡即時的調整圖片上物體的重要性。最後將重要性高的數個物體去做圖像檢索，找出含有這些對這個使用者是重要的物體的圖片。經由實驗證實，眼動軌跡輔助圖像檢索的確可以減少不重要的物體對圖像檢索的干擾，繼而可以提升圖像檢索系統的效能。 Recently, researches in Content-Based Image Retrieval (CBIR) focuses on incorporation of knowledge about human perception in the systems’ design and implementation process. This enables the design of more natural and intuitive image retrieval techniques in order to overcome some of the challenges faced by modern CBIR system such as the difficulty to extract important regions of an image. By researches of psychology, user’s eye tracking reflects his interest. So, in my CBIR system, user’s eye movements were used online to adjust the importance for objects in query image. Thus in my system, only those images with important objects will be retrieved. One experiment was performed: record the eye movement of participants on query images. Then compare my approach with a classic CBIR system according to performance. The results reveal that higher retrieval performance of my image retrieval system because of decreasing the influence of not importance objects to image retrieval system.
參考文獻:	[1] Nozha Boujemaa, Julien Fauqueur,and Valérie Gouet, “What`s beyond query by example?, “ International Conference on Image and Signal Processing, 2003. [2]Songhe Feng, De Xu, Xu Yang, and Aimin Wu, ”A Novel Region-Based Image Retrieval Algorithm Using Selective Visual Attention Model,” International Conference on Advanced Concept for Intelligent Vision system, pp.235-242,2005. [3] John M Henderson, and A Hollingworth, “High-Level Scene Perception, Annual Review of Psychology,” Annual Review of Psychology, vol. 50, pp.243-271, 1999. [4] Essig Kai , and Ritter Helge, “Visual-Based Image Retrieval (VBIR) - A New Approach for Natural and Intuitive Image Retrieval,” Proceedings of the 13th European Conference on Eye Movements, Aug.2005. [5] Scherffig Lasse, “It`s in Your Eyes - Gaze Based Image Retrieval in Context,” Edited by Hans H. Diebner, Institute for Basic Research, Karlsruhe, 2005. [6]O. Marques, L. M. Mayron,G. B. Borba, and H. R. Gamba, ”An Attention-Driven Model for Grouping Similar Images with Image Retrieval Applications,” Journal on Advances in Signal Processing, 2007. [7] O.K. Oyekoya, “Eye Tracking: A Perceptual Interface for Content Based Image Retrieval,” Ph.D. Thesis, Department of Electronic & Electrical Engineering Adastral Park Campus University College London, April 2007. [8] W Osberger, and A.J.Maeder, ”Automatic Identification of Perceptually Important Regions in an Image,” IEEE Proceedings, Fourteenth International Conference on Pattern Recognition, vol.1,pp. 701-704, 1998. [9]K Rayner, A. W. Inhoff, R.E. Morrison, M.L. Slowiaczek, ” Masking of foveal and parafoveal vision during eye fixations in reading.” Journal of Experiment Psychology：Human Perception and Performance, vol.7,pp. 167-179,1981. [10] Bryan C. Russell, Alexei A. Efros, Josef Sivic, William T. Freeman, and Andrew Zisserman, ” Using Multiple Segmentations to Discover Objects and their Extent in Image Collections,” IEEE Conference on Computer Vision and Pattern Recognition, 2006. [11] Dirk Walther and Christof Koch,” Modeling attention to salient proto-objects,” Neural networks, pp.1395 -1407, 2006. [12]Jing Zhang, Lansun Shen, and David Dagan Feng,”A Personalized Image Retrieval Based on Visual Perception,” Journal of Electronics (China), Jan. 2008.
描述:	碩士國立政治大學資訊科學學系 95753036 97
資料來源:	http://thesis.lib.nccu.edu.tw/record/#G0095753036
資料類型:	thesis
顯示於類別:	[資訊科學系] 學位論文

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檔案	描述	大小	格式	瀏覽次數
303601.pdf		116Kb	Adobe PDF2	820	檢視/開啟
303602.pdf		120Kb	Adobe PDF2	723	檢視/開啟
303603.pdf		116Kb	Adobe PDF2	768	檢視/開啟
303604.pdf		191Kb	Adobe PDF2	799	檢視/開啟
303605.pdf		121Kb	Adobe PDF2	888	檢視/開啟
303606.pdf		229Kb	Adobe PDF2	3479	檢視/開啟
303607.pdf		499Kb	Adobe PDF2	1259	檢視/開啟
303608.pdf		220Kb	Adobe PDF2	1091	檢視/開啟
303609.pdf		166Kb	Adobe PDF2	957	檢視/開啟
303610.pdf		86Kb	Adobe PDF2	753	檢視/開啟

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