Abstract
Like human vision, robot vision should be able to perceive three-dimensional (3-D) objects, i.e., be able to detect, verify, recognize, locate, inspect, and describe different 3-D objects. Although real objects are three-dimensional, humans can perceive them on the basis of visual data that is two-dimensional (2-D) and incomplete. Utilizing a variety of range cues (e.g., geometric, perspective, texture and shading variations, and occlusion), human perception maps visual data into 3D features and matches them with those of known models. Similar range cues are applicable to robot perception.
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Nitzan, D., Bolles, R., Kremers, J., Mulgaonkar, P. (1987). 3-D Vision for Robot Applications. In: Wong, A.K.C., Pugh, A. (eds) Machine Intelligence and Knowledge Engineering for Robotic Applications. NATO ASI Series, vol 33. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-87387-4_2
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DOI: https://doi.org/10.1007/978-3-642-87387-4_2
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