Salience computation in images based on perceptual distinctness |
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| Affiliation: | 1. Department of Psychiatry, Sant’Andrea Hospital, Sapienza University of Rome, Italy;2. Department of Mental Health, Santo Spirito Hospital, Rome, Italy;3. Psychiatry Residency Training Program, Faculty of Medicine and Psychology, Sapienza University of Rome, Sant''Andrea Hospital, Via di Grottarossa 1035-1039, 00189 Rome, Italy;4. Dept. of Neurosciences, Mental Health and Sensory Organs (NESMOS), Sant’Andrea Hospital, Sapienza University of Rome, Italy;1. School of Communication and Information Engineering, Shanghai University, Shanghai, China;2. Key Laboratory of Advanced Display and System Application, Ministry of Education, Shanghai University, Shanghai 200072, China;1. School of Computer Science, Beijing University of Posts and Telecommunications, Beijing 100876, China;2. Raytheon BBN Technologies, Cambridge, MA, USA;3. School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072, China;4. School of Information Engineering, Yangzhou University, Yangzhou 225127, China |
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| Abstract: | A salience computation approach based on perceptual distinctness is proposed in this paper that predicts human eye fixation locations in images. The approach uses a novel representation of pattern in a patch around a pixel such that discrimination between patterns is in compliance with distinctness between them in-terms of a few well-known perceptual cues. Image patches of different sizes (resolutions) are considered. The representations of the value at and pattern around a pixel in different features such as lightness, color and orientation are discriminated from all those in the rest of the image to compute salience at that pixel. The effectiveness of the proposed salience computation approach in generating salience maps closer to human eye fixation density maps is demonstrated by comparing it both qualitatively and quantitatively to other existing state-of-the-art salience computation approaches. Several synthetic images and psychological patterns, and real-life images from five well-known datasets are considered for this purpose. |
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| Keywords: | Perceptual distinctness Visual salience Human eye fixation |
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