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Robust Subspace Estimation Using Low-Rank Optimization: Theory and Applications

Description: Robust Subspace Estimation Using Low-Rank Optimization by Omar Oreifej, Mubarak Shah Estimated delivery 3-12 business days Format Paperback Condition Brand New Description 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. Publisher Description 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. Details ISBN 3319352482 ISBN-13 9783319352480 Title Robust Subspace Estimation Using Low-Rank Optimization Author Omar Oreifej, Mubarak Shah Format Paperback Year 2016 Pages 114 Publisher Springer International Publishing AG GE_Item_ID:143683005; About Us Grand Eagle Retail is the ideal place for all your shopping needs! With fast shipping, low prices, friendly service and over 1,000,000 in stock items - you're bound to find what you want, at a price you'll love! Shipping & Delivery Times Shipping is FREE to any address in USA. Please view eBay estimated delivery times at the top of the listing. Deliveries are made by either USPS or Courier. We are unable to deliver faster than stated. International deliveries will take 1-6 weeks. NOTE: We are unable to offer combined shipping for multiple items purchased. This is because our items are shipped from different locations. Returns If you wish to return an item, please consult our Returns Policy as below: Please contact Customer Services and request "Return Authorisation" before you send your item back to us. Unauthorised returns will not be accepted. Returns must be postmarked within 4 business days of authorisation and must be in resellable condition. Returns are shipped at the customer's risk. We cannot take responsibility for items which are lost or damaged in transit. For purchases where a shipping charge was paid, there will be no refund of the original shipping charge. Additional Questions If you have any questions please feel free to Contact Us. Categories Baby Books Electronics Fashion Games Health & Beauty Home, Garden & Pets Movies Music Sports & Outdoors Toys

Price: 69.24 USD

Location: Fairfield, Ohio

End Time: 2024-11-28T03:32:31.000Z

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Robust Subspace Estimation Using Low-Rank Optimization: Theory and Applications

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Restocking Fee: No

Return shipping will be paid by: Buyer

All returns accepted: Returns Accepted

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Refund will be given as: Money Back

ISBN-13: 9783319352480

Book Title: Robust Subspace Estimation Using Low-Rank Optimization

Number of Pages: VI, 114 Pages

Language: English

Publication Name: Robust Subspace Estimation Using Low-Rank Optimization : Theory and Applications

Publisher: Springer International Publishing A&G

Publication Year: 2016

Item Height: 0.3 in

Subject: Image Processing, Interactive & Multimedia, Computer Vision & Pattern Recognition

Type: Textbook

Item Weight: 68.5 Oz

Author: Mubarak Shah, Omar Oreifej

Subject Area: Computers

Item Length: 9.2 in

Item Width: 6.1 in

Series: The International Series in Video Computing Ser.

Format: Trade Paperback

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