Improving the Performance of Content Based Image Retrieval by Eye Tracking

• Main Authors: Jhang ,Jing Wun, 張京文
• Other Authors: Chen, Arbee L.P.
• Format: Others
• Language: zh-TW
• Published: 2008
• Online Access: http://ndltd.ncl.edu.tw/handle/38622664289719464473

碩士 === 國立政治大學 === 資訊科學學系 === 97 === 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.