Abstract
Human vision system can understand images quickly and accurately, but it is impossible to design a generic computer vision system to challenge this task at present. The most important reason is that computer vision community is lack of effective collaborations with visual psychologists, because current object recognition systems use only a small subset of visual cognition theory. We argue that it is possible to put forward a generic solution for image object recognition if the whole vision cognition theory of different schools and different levels can be systematically integrated into an inherent computing framework from the perspective of computer science. In this paper, we construct a generic object recognition solution, which absorbs the pith of main schools of vision cognition theory. Some examples illustrate the feasibility and validity of this solution.
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Wu, A., Xu, D., Yang, X., Zheng, J. (2005). Generic Solution for Image Object Recognition Based on Vision Cognition Theory. In: Wang, L., Jin, Y. (eds) Fuzzy Systems and Knowledge Discovery. FSKD 2005. Lecture Notes in Computer Science(), vol 3614. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11540007_166
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DOI: https://doi.org/10.1007/11540007_166
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28331-7
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