Detecting regions of interest using eye tracking for CBIR

Ren, Qingtao; Chen, Yongqiang; Zhang, Peng; Song, Dawei and Hou, Yuexian (2015). Detecting regions of interest using eye tracking for CBIR. In: SIGIR2015 Workshop on Neuro-Physiological Methods in IR Research, 13 Aug 2015, Santiago, Chile.

URL: https://docs.google.com/viewer?a=v&pid=sites&srcid...

Abstract

Identifying Regions of Interest (ROIs) in images has been shown an effective way to enhance the performance of Content Based Image Retrieval (CBIR). Most existing ROI identification methods are based on salience detection, and the identified ROIs may not be the regions that users are really interested in. While manual selection of ROIs can directly reflect users’ interests, it puts extra cognitive overhead to users. To alleviate these limitations, in this paper, we propose a novel eye-tracking based method to detect ROIs for CBIR, in an unobtrusive way. Experimental results have demonstrated that our model performed effectively compared with various state of the art methods.

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About

• Item ORO ID
• 44134
• Item Type
• Conference or Workshop Item
• Project Funding Details

• Funded Project Name	Project ID	Funding Body
  Not Set	2013CB329304	Chinese 973 Program
  Not Set	2014CB744604	Chinese 973 Program
  Not Set	2015AA015403	Chinese 863 Program
  Not Set	61272265	Natural Science Foundation of China
  Not Set	61402324	Natural Science Foundation of China

• Keywords
• content-based image retrieval; eye tracking; regions of interest
• Academic Unit or School
• Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
  Faculty of Science, Technology, Engineering and Mathematics (STEM)
• Copyright Holders
• © 2015 The Authors
• Related URLs
• • https://sites.google.com/site/neuroir201...(Other)
• Depositing User
• Dawei Song