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International Journal of Computer Vision

, Volume 104, Issue 1, pp 1–14 | Cite as

Linearized Alternating Direction Method with Adaptive Penalty and Warm Starts for Fast Solving Transform Invariant Low-Rank Textures

  • Xiang Ren
  • Zhouchen LinEmail author
Article

Abstract

Transform invariant low-rank textures (TILT) is a novel and powerful tool that can effectively rectify a rich class of low-rank textures in 3D scenes from 2D images despite significant deformation and corruption. The existing algorithm for solving TILT is based on the alternating direction method. It suffers from high computational cost and is not theoretically guaranteed to converge to a correct solution to the inner loop. In this paper, we propose a novel algorithm to speed up solving TILT, with guaranteed convergence for the inner loop. Our method is based on the recently proposed linearized alternating direction method with adaptive penalty. To further reduce computation, warm starts are also introduced to initialize the variables better and cut the cost on singular value decomposition. Extensive experimental results on both synthetic and real data demonstrate that this new algorithm works much more efficiently and robustly than the existing algorithm. It could be at least five times faster than the previous method.

Keywords

Transform invariant low-rank texutres Linearized alternating direction method with adaptive penalty Warm start Singular value decomposition 

Notes

Acknowledgments

Z. Lin is supported by the National Natural Science Foundation of China (Grant Nos. 61272341, 61231002, and 61121002).

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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.Department of Computer ScienceUniversity of Illinois at Urbana-champaignUrbanaUSA
  2. 2.Key Laboratory of Machine Perception (MOE), School of EECSPeking UniversityBeijingPeople’s Republic of China

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