By minimizing the rank of the matrix containing observations drawn from images, the authors demonstrate how to solve four fundamental computer vision problems, including video denosing, background subtraction, motion estimation, and activity recognition.
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By minimizing the rank of the matrix containing observations drawn from images, the authors demonstrate how to solve four fundamental computer vision problems, including video denosing, background subtraction, motion estimation, and activity recognition.
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Add this copy of Robust Subspace Estimation Using Low-Rank Optimization: to cart. $60.65, new condition, Sold by Ingram Customer Returns Center rated 5.0 out of 5 stars, ships from NV, USA, published 2016 by Springer.
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New. Print on demand Trade paperback (US). Glued binding. 114 p. Contains: Unspecified, Illustrations, black & white, Illustrations, color, Tables, black & white. The International Video Computing, 12.
Add this copy of Robust Subspace Estimation Using Low-Rank Optimization: to cart. $60.65, new condition, Sold by Ingram Customer Returns Center rated 5.0 out of 5 stars, ships from NV, USA, published 2014 by Springer International Publishing AG.
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Seller's Description:
New. Contains: Illustrations, black & white, Illustrations, color. International Series in Video Computing . VI, 114 p. 41 illus., 39 illus. in color. Intended for professional and scholarly audience.
