scholarly journals A fast algorithm for solving the Sylvester structured total least squares problem

2007 ◽  
Vol 87 (10) ◽  
pp. 2313-2319 ◽  
Author(s):  
Bingyu Li ◽  
Zhuojun Liu ◽  
Lihong Zhi
Keyword(s):  
Least Squares ◽  
Fast Algorithm ◽  
Total Least Squares ◽  
Least Squares Problem ◽  
Structured Total Least Squares

ROBUST NEURAL APPROACH FOR THE ESTIMATION OF THE ESSENTIAL PARAMETERS IN COMPUTER VISION

1999 ◽  
Vol 08 (03) ◽  
pp. 255-274 ◽  
Author(s):  
GIANSALVO CIRRINCIONE ◽  
MAURIZIO CIRRINCIONE
Keyword(s):  
Neural Network ◽  
Computer Vision ◽  
Image Segmentation ◽  
Least Squares ◽  
Total Least Squares ◽  
Outlier Rejection ◽  
Least Squares Problem ◽  
Case Deletion ◽  
Structured Total Least Squares ◽  
Deletion Diagnostics

The essential parameters approach is a well-known technique in computer vision for recovering the motion and scene parameters from a sequence of images. This approach has long been considered as suboptimal because of the underestimation of the effect of noise and outliers. This paper re-evaluates this method because it is correctly classified as a structured Total Least Squares problem and proposes very robust linear neurons for its solution. Then, a novel neural network, CASEDEL EXIN, which exploits these neurons together with the case deletion diagnostics, is introduced. It is not only very robust (outlier rejection), but is also able to identify the outliers. This fact can be exploited, for example, to refine the image segmentation.

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