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A Simple Method for...
A Simple Method for Subspace Estimation with Corrupted Columns
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- Larsson, Viktor (författare)
- Lund University,Lunds universitet,Matematik LTH,Matematikcentrum,Institutioner vid LTH,Lunds Tekniska Högskola,Mathematics (Faculty of Engineering),Centre for Mathematical Sciences,Departments at LTH,Faculty of Engineering, LTH
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- Olsson, Claes (författare)
- Lunds universitet,Lund University
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- Kahl, Fredrik, 1972 (författare)
- Chalmers University of Technology
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- Olsson, Carl (författare)
- Lund University,Lunds universitet,Matematik LTH,Matematikcentrum,Institutioner vid LTH,Lunds Tekniska Högskola,Mathematics (Faculty of Engineering),Centre for Mathematical Sciences,Departments at LTH,Faculty of Engineering, LTH
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(creator_code:org_t)
- ISBN 9781467383905
- 2016
- 2016
- Engelska.
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Ingår i: Proceedings of the IEEE International Conference on Computer Vision. - 1550-5499. - 9781467383905 ; 2016-February, s. 841-849
- Relaterad länk:
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http://dx.doi.org/10...
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https://research.cha...
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https://doi.org/10.1...
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https://lup.lub.lu.s...
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Abstract
Ämnesord
Stäng
- This paper presents a simple and effective way of solving the robust subspace estimation problem where the corruptions are column-wise. The method we present can handle a large class of robust loss functions and is simple to implement. It is based on Iteratively Reweighted Least Squares (IRLS) and works in an iterative manner by solving a weighted least-squares rank-constrained problem in every iteration. By considering the special case of column-wise loss functions, we show that each such surrogate problem admits a closed form solution. Unlike many other approaches to subspace estimation, we make no relaxation of the low-rank constraint and our method is guaranteed to produce a subspace estimate with the correct dimension. Subspace estimation is a core problem for several applications in computer vision. We empirically demonstrate the performance of our method and compare it to several other techniques for subspace estimation. Experimental results are given for both synthetic and real image data including the following applications: linear shape basis estimation, plane fitting and non-rigid structure from motion.
Ämnesord
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Medicinteknik -- Medicinsk bildbehandling (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Medical Engineering -- Medical Image Processing (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datorseende och robotik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Vision and Robotics (hsv//eng)
Nyckelord
- Optimization
- Estimation
- Closed-form solutions
- Robustness
- Computer vision
- Convergence
- Shape
- Closed-form solutions
- Computer vision
- Convergence
- Estimation
- Optimization
- Robustness
- Shape
Publikations- och innehållstyp
- kon (ämneskategori)
- ref (ämneskategori)
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