Recognition Via High-dimensional Data Classification
A method is disclosed for recognition of high-dimensional data in the presence of occlusion, including: receiving a target data that includes an occlusion and is of an unknown class, wherein the target data includes a known object; sampling a plurality of training data files comprising a plurality of distinct classes of the same object as that of the target data; and identifying the class of the target data through linear superposition of the sampled training data files using l1 minimization, wherein a linear superposition with a sparsest number of coefficients is used to identify the class of the target data.
MA YI [US]; YANG ALLEN YANG [US]; WRIGHT JOHN NORBERT [US]; WAGNER ANDREW WILLIAM [US]
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