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S. Ullman, R. Basri, "Recognition by Linear Combinations of Models," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 13, no. 10, pp. 9921006, October, 1991.  
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@article{ 10.1109/34.99234, author = {S. Ullman and R. Basri}, title = {Recognition by Linear Combinations of Models}, journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence}, volume = {13}, number = {10}, issn = {01628828}, year = {1991}, pages = {9921006}, doi = {http://doi.ieeecomputersociety.org/10.1109/34.99234}, 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  Recognition by Linear Combinations of Models IS  10 SN  01628828 SP992 EP1006 EPD  9921006 A1  S. Ullman, A1  R. Basri, PY  1991 KW  model combination; image combination; rigid transformations; linear combinations; visual object recognition; sharp edges; smooth bounding contours; computerised pattern recognition; computerised picture processing VL  13 JA  IEEE Transactions on Pattern Analysis and Machine Intelligence ER   
An approach to visual object recognition in which a 3D object is represented by the linear combination of 2D images of the object is proposed. It is shown that for objects with sharp edges as well as with smooth bounding contours, the set of possible images of a given object is embedded in a linear space spanned by a small number of views. For objects with sharp edges, the linear combination representation is exact. For objects with smooth boundaries, it is an approximation that often holds over a wide range of viewing angles. Rigid transformations (with or without scaling) can be distinguished from more general linear transformations of the object by testing certain constraints placed on the coefficients of the linear combinations. Three alternative methods of determining the transformation that matches a model to a given image are proposed.
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