Abstract
We consider the problem of finding a known two- dimensional object in an image, or verifying that it does not appear in the image. We adopt the strategy of doing a fast scan for potential places in the image where the object could be; we call this scan pose proposal. Each pose hypothesis is a set of edges that correspond to a subset of the transformed object bouńdary. Our algorithm works by finding U- shaped segments of object boundaries, doing a quick match process between U- shaped segments in the image and the model, and combining the matches into overall pose hypotheses. Analysis and experiments show that the algorithm runs efficiently, and does a good job of discarding all but a few spots in the image as possible pose hypotheses.
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© 1996 Springer-Verlag Berlin Heidelberg
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Tagare, H., McDermott, D. (1996). Model-Based pose proposal for 2-D object recognition. In: Borges, D.L., Kaestner, C.A.A. (eds) Advances in Artificial Intelligence. SBIA 1996. Lecture Notes in Computer Science, vol 1159. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61859-7_16
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DOI: https://doi.org/10.1007/3-540-61859-7_16
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