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    戚金清

    • 副教授       硕士生导师
    • 性别:男
    • 毕业院校:东京工业大学
    • 学位:博士
    • 所在单位:信息与通信工程学院
    • 学科:通信与信息系统. 信号与信息处理
    • 电子邮箱:jinqing@dlut.edu.cn

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    Predicting human gaze with multi-level information

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    论文类型:期刊论文

    第一作者:Zhang, Xiaoning

    通讯作者:Lu, HC (reprint author), Dalian Univ Technol, Sch Informat & Commun Engn, Dalian 116023, Peoples R China.

    合写作者:Xiao, Di,Li, Jianhua,Qi, Jinqing,Lu, Huchuan

    发表时间:2018-06-01

    发表刊物:SIGNAL PROCESSING

    收录刊物:SCIE、EI

    卷号:147

    页面范围:92-100

    ISSN号:0165-1684

    关键字:Attention; Eye fixation; Feature; Adaptive weight learning

    摘要:Eye fixation models, which try to quantitatively predict human eye attended areas in visual fields, have received increasing interest in recent years. In this paper, a novel framework is proposed for the detection of eye fixations. First, a multi-channel detection module, which extracts information of color contrast, salient object proposals and center bias from input image, is conducted to introduce various useful information into the subsequent fixations detection. In salient object detection channel, we employ the multi-instance learning (MIL) algorithm to determine which object proposal can attract attention, which avoids the fuzzyness of positive sample selection. Second, an adaptive weighted fusion method achieved by deep learning framework is proposed to fuse the multi-level information (i.e., contrast, objective, center bias) together for the detection of fixations, so that the integration of information between each level becomes more scientific. Finally, the detection result is optimized by embedding semantic information. Experimental results show that the algorithm has achieved competitive results in MIT1003, MIT300 and Toronto120 dataset. (C) 2018 Elsevier B.V. All rights reserved.