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Non-orthogonal binary subspace and its applications in computer vision
2005
Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1
This paper presents a novel approach that represents an image or a set of images using a nonorthogonal binary subspace (NBS) spanned by boxlike base vectors. These base vectors possess the property that the inner product operation with them can be computed very efficiently. We investigate the optimized orthogonal matching pursuit method for finding the best NBS base vectors. It is demonstrated in this paper how the NBS based expansion can be applied to speed up several common computer vision
doi:10.1109/iccv.2005.169
dblp:conf/iccv/TaoCT05
fatcat:ntw42mj2lrbmrcc5weaw4iasom