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作 者:Zhang Jing Shen Lansun David Dagan Feng
机构地区:[1]Signal & Information Processing Lab., Beijing University of Technology, Beijing 100022, China [2]School of Information Technologies, the University of Sydney, NSW 2006, Australia [3]Department of Electronic and Information Engineering, Hong Kong Polytechnic University, Hong Kong, China
出 处:《Journal of Electronics(China)》2008年第1期129-133,共5页电子科学学刊(英文版)
基 金:Supported by the National Natural Science Foundation of China (No.60472036, No.60431020, No.60402036);the Natural Science Foundation of Beijing (No.4042008);and Ph.D. Foundation of Ministry of Education (No.20040005015).
摘 要:A new scheme named personalized image retrieval technique based on visual perception is proposed in this letter, whose motive is to narrow the semantic gap by directly perceiving user's visual information. It uses visual attention model to segment image regions and eye-tracking technique to record fixations. Visual perception is obtained by analyzing the fixations in regions to measure gaze interests. Integrating visual perception into attention model is to detect the Regions Of Interest (ROIs), whose features are extracted and analyzed, then feedback interests to optimize the results and construct user profiles.A new scheme named personalized image retrieval technique based on visual perception is proposed in this letter, whose motive is to narrow the semantic gap by directly perceiving user's visual information. It uses visual attention model to segment image regions and eye-tracking technique to record fixations. Visual perception is obtained by analyzing the fixations in regions to measure gaze interests. Integrating visual perception into attention model is to detect the Regions Of Interest (ROIs), whose features are extracted and analyzed, then feedback interests to optimize the results and construct user profiles.
关 键 词:Personalized image retrieval Visual perception Semantic gap Regions Of Interest (ROIs)
分 类 号:TP391[自动化与计算机技术—计算机应用技术]
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