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Fast kernel sparse representation

Li, Hanxi; Gao, Yongsheng; Sun, Jun


Two efficient algorithms are proposed to seek the sparse representation on high-dimensional Hilbert space. By proving that all the calculations in Orthogonal Match Pursuit (OMP) are essentially inner-product combinations, we modify the OMP algorithm to apply the kernel-trick. The proposed Kernel OMP (KOMP) is much faster than the existing methods, and illustrates higher accuracy in some scenarios. Furthermore, inspired by the success of group-sparsity, we enforce a rigid group-sparsity...[Show more]

CollectionsANU Research Publications
Date published: 2011
Type: Conference paper
Source: A Novel Illumination-Invariant Loss for Monocular 3D Pose Estimation
DOI: 10.1109/DICTA.2011.20


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