Salient object detection with low-rank approximation and ℓ2,1-norm minimization

作者：

Highlights：

• Propose an efficient algorithm for low-rank approximation

• Develop a new method with proved convergence to learn sparsity

• Incorporate low-rank recovery and sparse coding into one joint framework

• Validate the proposed algorithm with parameter sensitivity and performance

摘要

•Propose an efficient algorithm for low-rank approximation•Develop a new method with proved convergence to learn sparsity•Incorporate low-rank recovery and sparse coding into one joint framework•Validate the proposed algorithm with parameter sensitivity and performance

论文关键词：Compute vision,Image processing,Saliency detection,Sparse coding,Low-rank approximation,ℓ2,1 -norm minimization

论文评审过程：Received 24 January 2016, Revised 12 September 2016, Accepted 21 October 2016, Available online 15 November 2016, Version of Record 4 December 2016.

论文官网地址：https://doi.org/10.1016/j.imavis.2016.10.008