TY - GEN
T1 - Clustering appearances of 3D objects
AU - Basri, Ronen
AU - Roth, Dan
AU - Jacobs, David
N1 - Copyright:
Copyright 2011 Elsevier B.V., All rights reserved.
PY - 1998
Y1 - 1998
N2 - We introduce a method for unsupervised clustering of images of 3D objects. Our method examines the space of all images and partitions the images into sets that form smooth and parallel surfaces in this space. It further uses sequences of images to obtain more reliable clustering. Finally, since our method relies on a non-Euclidean similarity measure we introduce algebraic techniques for estimating local properties of these surfaces without first embedding the images in a Euclidean space. We demonstrate our method by applying it to a large database of images.
AB - We introduce a method for unsupervised clustering of images of 3D objects. Our method examines the space of all images and partitions the images into sets that form smooth and parallel surfaces in this space. It further uses sequences of images to obtain more reliable clustering. Finally, since our method relies on a non-Euclidean similarity measure we introduce algebraic techniques for estimating local properties of these surfaces without first embedding the images in a Euclidean space. We demonstrate our method by applying it to a large database of images.
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U2 - 10.1109/CVPR.1998.698639
DO - 10.1109/CVPR.1998.698639
M3 - Conference contribution
AN - SCOPUS:0032293333
SN - 0818684976
T3 - Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
SP - 414
EP - 420
BT - Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
T2 - Proceedings of the 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Y2 - 23 June 1998 through 25 June 1998
ER -