Fast kernel sparse representation
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]
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|Source:||A Novel Illumination-Invariant Loss for Monocular 3D Pose Estimation|
|01_Li_Fast_kernel_sparse_2011.pdf||287.43 kB||Adobe PDF||Request a copy|
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