Abstract
The conventional approaches to 3D object recognition are mostly based on 3D object models. They include model-based feature grouping [91], model-based geometrical reasoning [16], constrained search [49], model fitting guided by local feature [18], feature based geometric hashing [83], automatic generation of search trees [75]. All these approaches rely on explicit 3D data as object model in this or that way. Unfortunately, however, 3D data are not always available for every object. In the case of manufactured objects, the data used in designing may be available. If one has to obtain the data by vision, then the difficulty is that there is still no algorithm available that works in every kind of environment.
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© 1996 Springer Science+Business Media Dordrecht
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Xu, G., Zhang, Z. (1996). 3D Object Recognition and Localization with Model Views. In: Epipolar Geometry in Stereo, Motion and Object Recognition. Computational Imaging and Vision, vol 6. Springer, Dordrecht. https://doi.org/10.1007/978-94-015-8668-9_8
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DOI: https://doi.org/10.1007/978-94-015-8668-9_8
Publisher Name: Springer, Dordrecht
Print ISBN: 978-90-481-4743-4
Online ISBN: 978-94-015-8668-9
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