Abstract
This paper proposes a 3D object recognition model that integrates the image segmentation and the correspondence estimation based on bidirectional processing. The model can cope with both the view variation and the multiple objects occluding each other in the image. We evaluated the performance of the proposed model through computer experiments using gray-level images of 3D objects.
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© 1997 Springer-Verlag Berlin Heidelberg
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Fujita, T., Ando, H. (1997). Image segmentation for 3D object recognition using bidirectional networks. In: Gerstner, W., Germond, A., Hasler, M., Nicoud, JD. (eds) Artificial Neural Networks — ICANN'97. ICANN 1997. Lecture Notes in Computer Science, vol 1327. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0020274
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DOI: https://doi.org/10.1007/BFb0020274
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