Paper
1 September 1991 Coupled depth-slope model based on augmented Lagrangian techniques
David Suter
Author Affiliations +
Abstract
The reconstruction of quantities from a scene can be formulated using regularization. The regularization formulation can be reduced to a formulation involving coupled sub-problems by considering the problem a one of simultaneously estimating different orders of derivatives. The starting point of the author's work is to ensure correspondence between the sub-problems by Augmented Lagrangian techniques. The finite element discretization of such problems is now firmly placed within a 'mixed finite element' formalism. For digital solution of these problems there are many iterative methods (including Uzawa's method, Arrow/Hurwicz method, conjugate directions) and associated pre-condition strategies. For future, real-time operation, it is often suggested that an analog network implementation be developed. A previous model for this is the Harris coupled depth-slope approach. As an analog implementation strategy, the 'neural network' optimization method of Platt is used to derive an analog resistive networks within the most general framework. Modifications to the basic approach to implement segmentation and viewpoint invariance are also discussed.
© (1991) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
David Suter "Coupled depth-slope model based on augmented Lagrangian techniques", Proc. SPIE 1570, Geometric Methods in Computer Vision, (1 September 1991); https://doi.org/10.1117/12.48419
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KEYWORDS
Analog electronics

Chemical elements

Visualization

Computer vision technology

Machine vision

Data modeling

Image segmentation

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