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Prediction of Human Eye Fixation by a Single Filter

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Abstract

Saliency modeling has played an important part in computer vision studies over the past 30 years. Many state-of-the-art models adopted complex mathematical and machine learning theories. In this paper, a simple and effective visual attention model is proposed. We find that a single fixed template is enough for saliency map generation; this idea is inspired by the receptive field of the human visual system. All that is needed is to convolve the input image with this template with additional post-processing. Experiments show that our model is extremely fast and performs better than state-of-the-art models in human eye fixation prediction.

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Acknowledgments

This work is supported by the Doctoral Dissertation Innovation Fund of Huazhong University of Science and Technology.

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Authors and Affiliations

  1. School of Software Engineering, Huazhong University of Science and Technology, Wuhan, China

    He Tang & Chuanbo Chen

  2. First Clinical Medical College, Guangdong Medical University, Zhanjiang, China

    Yanan Bie

Authors
  1. He Tang
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  2. Chuanbo Chen
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  3. Yanan Bie
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Corresponding author

Correspondence to Chuanbo Chen.

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Tang, H., Chen, C. & Bie, Y. Prediction of Human Eye Fixation by a Single Filter. J Sign Process Syst 87, 197–202 (2017). https://doi.org/10.1007/s11265-016-1131-8

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  • DOI: https://doi.org/10.1007/s11265-016-1131-8

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