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S.J. Dickinson, A.P. Pentland, A. Rosenfeld, "3D Shape Recovery Using Distributed Aspect Matching," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 14, no. 2, pp. 174198, February, 1992.  
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@article{ 10.1109/34.121788, author = {S.J. Dickinson and A.P. Pentland and A. Rosenfeld}, title = {3D Shape Recovery Using Distributed Aspect Matching}, journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence}, volume = {14}, number = {2}, issn = {01628828}, year = {1992}, pages = {174198}, doi = {http://doi.ieeecomputersociety.org/10.1109/34.121788}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }  
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TY  JOUR JO  IEEE Transactions on Pattern Analysis and Machine Intelligence TI  3D Shape Recovery Using Distributed Aspect Matching IS  2 SN  01628828 SP174 EP198 EPD  174198 A1  S.J. Dickinson, A1  A.P. Pentland, A1  A. Rosenfeld, PY  1992 KW  3D shape recovery; pattern recognition; 3D volumetric primitives; picture processing; projected primitive surfaces; distributed aspect matching; hierarchical aspect representation; conditional probabilities; region segmentation; probabilities; connectivity; vocabulary; pattern recognition; picture processing; probability VL  14 JA  IEEE Transactions on Pattern Analysis and Machine Intelligence ER   
An approach to the recovery of 3D volumetric primitives from a single 2D image is presented. The approach first takes a set of 3D volumetric modeling primitives and generates a hierarchical aspect representation based on the projected surfaces of the primitives; conditional probabilities capture the ambiguity of mappings between levels of the hierarchy. From a region segmentation of the input image, the authors present a formulation of the recovery problem based on the grouping of the regions into aspects. No domainindependent heuristics are used; only the probabilities inherent in the aspect hierarchy are exploited. Once the aspects are recovered, the aspect hierarchy is used to infer a set of volumetric primitives and their connectivity. As a front end to an object recognition system, the approach provides the indexing power of complex 3D objectcentered primitives while exploiting the convenience of 2D viewercentered aspect matching; aspects are used to represent a finite vocabulary of 3D parts from which objects can be constructed.
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