Robust Subspace Estimation Using Low-Rank Optimization: Theory and Applications (The International Series in Video Computing, 12) - Hardcover
Synopsis
Various fundamental applications in computer vision and machine learning require finding the basis of a certain subspace. Examples of such applications include face detection, motion estimation, and activity recognition. An increasing interest has been recently placed on this area as a result of significant advances in the mathematics of matrix rank optimization. Interestingly, robust subspace estimation can be posed as a low-rank optimization problem, which can be solved efficiently using techniques such as the method of Augmented Lagrange Multiplier. In this book, the authors discuss fundamental formulations and extensions for low-rank optimization-based subspace estimation and representation. 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.
"synopsis" may belong to another edition of this title.
Other Popular Editions of the Same Title
Search results for Robust Subspace Estimation Using Low-Rank Optimization:...
Seller Image
Robust Subspace Estimation Using Low-Rank Optimization : Theory and Applications
Seller: GreatBookPrices, Columbia, MD, U.S.A.
Seller rating 5 out of 5 stars
Condition: New. Seller Inventory # 21054948-n
Stock Image
Oreifej:Robust Subspace Estimation Usin (eng)
Print on DemandSeller: Brook Bookstore On Demand, Napoli, NA, Italy
Seller rating 4 out of 5 stars
Condition: new. Questo è un articolo print on demand. Seller Inventory # 962d8323d76d5634335af5f1d325f3ec
Stock Image
Robust Subspace Estimation Using Low-Rank Optimization: Theory and Applications (The International Series in Video Computing, 12)
Seller: Lucky's Textbooks, Dallas, TX, U.S.A.
Seller rating 5 out of 5 stars
Condition: New. Seller Inventory # ABLIING23Mar3113020086742
Seller Image
Robust Subspace Estimation Using Low-Rank Optimization : Theory and Applications
Seller: GreatBookPrices, Columbia, MD, U.S.A.
Seller rating 5 out of 5 stars
Condition: As New. Unread book in perfect condition. Seller Inventory # 21054948
Stock Image
Robust Subspace Estimation Using Low-Rank Optimization: Theory and Applications (The International Series in Video Computing, 12)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
Condition: New. In. Seller Inventory # ria9783319041834_new
Buy New
US$ 67.02
Shipping:
US$ 15.87
From United Kingdom to U.S.A.
Quantity: Over 20 available
Seller Image
Robust Subspace Estimation Using Low-Rank Optimization : Theory and Applications
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: New. Seller Inventory # 21054948-n
Buy New
US$ 67.01
Shipping:
US$ 19.87
From United Kingdom to U.S.A.
Quantity: Over 20 available
Stock Image
Robust Subspace Estimation Using Low-Rank Optimization:Theory and Applications
Seller: Books Puddle, New York, NY, U.S.A.
Seller rating 4 out of 5 stars
Condition: New. pp. 112. Seller Inventory # 26105020717
Seller Image
Robust Subspace Estimation Using Low-Rank Optimization
Published by
Springer International Publishing Apr 2014, 2014
ISBN 10: 3319041835
ISBN 13: 9783319041834
New
Hardcover
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Various fundamental applications in computer vision and machine learning require finding the basis of a certain subspace. Examples of such applications include face detection, motion estimation, and activity recognition. An increasing interest has been recently placed on this area as a result of significant advances in the mathematics of matrix rank optimization. Interestingly, robust subspace estimation can be posed as a low-rank optimization problem, which can be solved efficiently using techniques such as the method of Augmented Lagrange Multiplier. In this book, the authors discuss fundamental formulations and extensions for low-rank optimization-based subspace estimation and representation. 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. 120 pp. Englisch. Seller Inventory # 9783319041834
Seller Image
Robust Subspace Estimation Using Low-Rank Optimization : Theory and Applications
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: As New. Unread book in perfect condition. Seller Inventory # 21054948
Buy Used
US$ 76.07
Shipping:
US$ 19.87
From United Kingdom to U.S.A.
Quantity: Over 20 available
Stock Image
Robust Subspace Estimation Using Low-Rank Optimization:Theory and Applications
Print on DemandSeller: Majestic Books, Hounslow, United Kingdom
Seller rating 4 out of 5 stars
Condition: New. Print on Demand pp. 112. Seller Inventory # 104186610
Buy New
US$ 89.05
Shipping:
US$ 8.61
From United Kingdom to U.S.A.
Quantity: 4 available