Abstract
In natural scenes, objects are often partially occluded. Nonetheless, our visual system can readily complete an object shape from available information and perceive it as a whole, a process known as amodal completion. Although implementation of this completion process is an important issue, visual computation for completion, based on both the local continuity of contours and on global regularities, such as symmetry, has received little attention. Here, we show a novel neurocomputational model based on recent physiological findings, in particular those in visual area V4. The model enables amodal completion through the evaluation of a global constellation of features describing a shapefs contours.
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Sakamoto, K., Kumada, T., Yano, M. (2010). A Computational Model That Enables Global Amodal Completion Based on V4 Neurons. In: Wong, K.W., Mendis, B.S.U., Bouzerdoum, A. (eds) Neural Information Processing. Theory and Algorithms. ICONIP 2010. Lecture Notes in Computer Science, vol 6443. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17537-4_2
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DOI: https://doi.org/10.1007/978-3-642-17537-4_2
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