scholarly journals SPARSE REPRESENTATIONS WITH DATA FIDELITY TERM VIA AN ITERATIVELY REWEIGHTED LEAST SQUARES ALGORITHM

2007 ◽  
Author(s):  
BRENDT WOHLBERG ◽  
PAUL RODRIGUEZ
Keyword(s):  
Least Squares ◽  
Sparse Representations ◽  
Iteratively Reweighted Least Squares ◽  
Data Fidelity ◽  
Fidelity Term ◽  
Least Squares Algorithm

scholarly journals Robust Semiautomatic 2D-to-3D Conversion with Welsch M-Estimator for Data Fidelity

2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Hongxing Yuan ◽  
Shaoqun Wu ◽  
Peng An ◽  
Chunya Tong ◽  
You Zheng ◽  
...  
Keyword(s):  
Least Squares ◽  
State Of The Art ◽  
The State ◽  
Iteratively Reweighted Least Squares ◽  
Competitive Performance ◽  
M Estimator ◽  
2D To 3D Conversion ◽  
Data Fidelity ◽  
Similar Depth ◽  
2D To 3D

Semiautomatic 2D-to-3D conversion plays an important role in generating 3D contents for display. However, most existing methods assume that user scribbles are perfectly correct, and only give acceptable results when user provides accurate labels. To address this problem, Welsch M-estimator data fidelity is used to resist erroneous scribbles. The Welsch M-estimator data fidelity which is able to alleviate the influence of inaccurate scribbles has theoretical guarantee by means of its redescending property. First, the Welsch M-estimator is introduced to measure the fidelity between estimated depth and user provided depth; then local smoothness is built by using color weighted Welsch M-estimator to make neighboring pixels with similar colors have similar depth values. Finally, we solve the problem using generalized iteratively reweighted least squares algorithm. Experiments demonstrate that our method obtains competitive performance in the absence of inaccurate scribbles and outperforms the state of the art both visually and quantitatively in the presence of inaccurate scribbles.

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