Abstract
Selective attention works throughout the whole process of vision information processing. Existing attention models concentrate on its role in feature extraction in initial stage, but ignore role of attention in other stages. In this paper, we extend attention to middle stage, especially in guiding perceptual grouping. Selective attention functions in two aspects. One is to select the most salient primitive as grouping seed. The other is to organize groups and decide their pop-out sequence. Compared with traditional attention models, our model judges primitive salience according to global properties rather than local ones. And focus of attention shifts in unit of perceptual object rather than spatial region. These two improvements boost the model’s grouping quality and more fit to high stage of vision information processing. Experiments and quantitative analysis testify our model’s good performance in certain class of images.
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Zou, Q., Luo, S., Li, J. (2005). Selective Attention Guided Perceptual Grouping Model. In: Wang, L., Chen, K., Ong, Y.S. (eds) Advances in Natural Computation. ICNC 2005. Lecture Notes in Computer Science, vol 3610. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539087_117
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DOI: https://doi.org/10.1007/11539087_117
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28323-2
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