Abstract
Image matting is an important task in image and video editing. In this paper we propose a novel automatic matting approach, which can provide a good set of constraints without human intervention. We use the attention shift trace in a temporal sequence as the useful constraints for matting algorithm instead of user-specified “scribbles”. Then we propose a modified visual selective attention mechanism which considered two Gestalt rules (proximity & similarity) for shifting the processing focus. Experimental results on real-world data show that the constraints are useful. Distinct from previous approaches, the algorithm presents the advantage of being biologically plausible.
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Sun, W., Luo, S., Wu, L. (2010). A Biologically-Inspired Automatic Matting Method Based on Visual Attention. In: Zhang, L., Lu, BL., Kwok, J. (eds) Advances in Neural Networks - ISNN 2010. ISNN 2010. Lecture Notes in Computer Science, vol 6064. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13318-3_22
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DOI: https://doi.org/10.1007/978-3-642-13318-3_22
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