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Visual Attention Region Prediction Based on Eye Tracking Using Fuzzy Inference
http://hdl.handle.net/10098/8434
http://hdl.handle.net/10098/84342834a96c-1dd8-4591-acd6-3321a260c88e
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JACIII.htm (821 Bytes)
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Fujipress_JACIII-18-4-5 (1.2 MB)
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Item type | 学術雑誌論文 / Journal Article(1) | |||||
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公開日 | 2014-07-31 | |||||
タイトル | ||||||
タイトル | Visual Attention Region Prediction Based on Eye Tracking Using Fuzzy Inference | |||||
言語 | ||||||
言語 | eng | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | Visual Attention | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | Eye Tracking | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | Neural Network | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | Saliency Map | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | Fuzzy Inference | |||||
資源タイプ | ||||||
資源タイプ識別子 | http://purl.org/coar/resource_type/c_1843 | |||||
資源タイプ | other | |||||
著者 |
Wang, Mao
× Wang, Mao× Maeda, Yoichiro× Takahashi, Yasutake |
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抄録 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | Visual attention region prediction has attracted the attention of intelligent systems researchers because it makes the interaction between human beings and intelligent nonhuman agents to be more intelligent. Visual attention region prediction uses multiple input factors such as gestures, face images and eye gaze position. Physically, disabled persons may find it difficult to move in some way. In this paper, we propose using gaze position estimation as input to a prediction system achieved by extracting image features. Our approach is divided into two parts: user gaze estimation and visual attention region inference. The neural network has been used in user gaze estimation as the decision making unit, following which the user gaze position at the computer screen is then estimated. We proposed that prediction in visual attention region inference of the visual attention region be inferred by using fuzzy inference after image feature maps and saliency maps have been extracted and computed. User experiments conducted to evaluate the prediction accuracy of our proposed method surveyed prediction results. These results indicated that the prediction we proposed performs better at the attention regions position prediction level depending on the image. | |||||
内容記述 | ||||||
内容記述タイプ | Other | |||||
内容記述 | Journal of Advanced Computational Intelligence and Intelligent Informatics Vol.18 No.4 p499-510 | |||||
書誌情報 |
Journal of Advanced Computational Intelligence and Intelligent Informatics 巻 18, 号 4, p. 499-510, 発行日 2014-07 |
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出版者 | ||||||
出版者 | Fuji Technology Press | |||||
ISSN | ||||||
収録物識別子タイプ | ISSN | |||||
収録物識別子 | 13430130 | |||||
書誌レコードID | ||||||
識別子タイプ | NCID | |||||
関連識別子 | TD00007233 | |||||
著者版フラグ | ||||||
出版タイプ | AO | |||||
出版タイプResource | http://purl.org/coar/version/c_b1a7d7d4d402bcce |