Abstract
This paper considers a model-based approach to identifying and locating known 3D objects from 2D images. The method is based on geometric feature matching of the model and image data, where both are represented in terms of local geometric features. This paper extends and refines previous work on feature matching using transformation constraint methods by detailing the case of full 3D objects represented as point features and developing geometric algorithms based on conservative approximations to the previously presented general algorithm which are much more computationally feasible.
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© 1996 Springer-Verlag Berlin Heidelberg
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Cass, T.A. (1996). Robust affine structure matching for 3D object recognition. In: Buxton, B., Cipolla, R. (eds) Computer Vision — ECCV '96. ECCV 1996. Lecture Notes in Computer Science, vol 1064. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0015560
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DOI: https://doi.org/10.1007/BFb0015560
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