Abstract
We present an approach general enough to apply to recognition of complex rigid 3D objects from either a single intensity image or a single range image. Within the general paradigm of recognition by alignment, we address (1) definition and detection of primitives, (2) indexing to model hypotheses, (3) constructing view sphere models from sensed data, and (4) aligning model and sensed features for verification. The overall paradigm is not new, but rather fits within theory already espoused by Lowe and Ullman and many others: our position is therefore both a synthesis of and endorsement of much other work toward recognition of rigid free-form objects.
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© 1995 Springer-Verlag Berlin Heidelberg
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Stockman, G. (1995). Object representation for recognition-by-alignment. In: Hebert, M., Ponce, J., Boult, T., Gross, A. (eds) Object Representation in Computer Vision. ORCV 1994. Lecture Notes in Computer Science, vol 994. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-60477-4_5
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DOI: https://doi.org/10.1007/3-540-60477-4_5
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