Abstract
Human attention plays an important role in human visual system. We assume that the Gestalt law is one of important factors to guide human selective attention. In this paper, we present a series of studies in which we hypothesized that regions of image that get more attention in an object recognition task, confirm to one or more gestalt principles and subconsciously attract human attention which eventually help in object recognition. In our study, we collected attention parts of images by analyzing eye movement of participants. Then we compared Gestalt scores of high attention parts with those of nonattended random parts. Our results suggest that continuity and symmetry of features attract human attention. We argue that an approach to analyze parts with high Gestalt scores can yield better than analyzing random parts of image in object recognition.
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Shen, J., Ojha, A., Lee, M. (2013). Role of Gestalt Principles in Selecting Attention Areas for Object Recognition. In: Lee, M., Hirose, A., Hou, ZG., Kil, R.M. (eds) Neural Information Processing. ICONIP 2013. Lecture Notes in Computer Science, vol 8226. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-42054-2_12
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DOI: https://doi.org/10.1007/978-3-642-42054-2_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-42053-5
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