NDLI: Content-based image retrieval using a combination of visual features and eye tracking data

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Content-based image retrieval using a combination of visual features and eye tracking data

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Content-based image retrieval using a combination of visual features and eye tracking data

Content Provider	ACM Digital Library
Author	Chi, Zheru Zhang, Yun Fu, Hong Feng, Dagan Liang, Zhen
Abstract	Image retrieval technology has been developed for more than twenty years. However, the current image retrieval techniques cannot achieve a satisfactory recall and precision. To improve the effectiveness and efficiency of an image retrieval system, a novel content-based image retrieval method with a combination of image segmentation and eye tracking data is proposed in this paper. In the method, eye tracking data is collected by a non-intrusive table mounted eye tracker at a sampling rate of 120 Hz, and the corresponding fixation data is used to locate the human's Regions of Interest (hROIs) on the segmentation result from the JSEG algorithm. The hROIs are treated as important informative segments/objects and used in the image matching. In addition, the relative gaze duration of each hROI is used to weigh the similarity measure for image retrieval. The similarity measure proposed in this paper is based on a retrieval strategy emphasizing the most important regions. Experiments on 7346 Hemera color images annotated manually show that the retrieval results from our proposed approach compare favorably with conventional content-based image retrieval methods, especially when the important regions are difficult to be located based on visual features.
Starting Page	41
Ending Page	44
Page Count	4
File Format	PDF
ISBN	9781605589947
DOI	10.1145/1743666.1743675
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2010-03-22
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Content-based image retrieval (cbir) Fixation Similarity measure Eye tracking Visual perception
Content Type	Text
Resource Type	Article

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