Publication Date:
1990-06-08
Description:
A large number of computer vision algorithms for finding intensity edges, computing motion, depth, and color, and recovering the three-dimensional shape of objects have been developed within the framework of minimizing an associated "energy" or "cost" functional. Particularly successful has been the introduction of binary variables coding for discontinuities in intensity, optical flow field, depth, and other variables, allowing image segmentation to occur in these modalities. The associated nonconvex variational functionals can be mapped onto analog, resistive networks, such that the stationary voltage distribution in the network corresponds to a minimum of the functional. The performance of an experimental analog very-large-scale integration (VLSI) circuit implementing the nonlinear resistive network for the problem of two-dimensional surface interpolation in the presence of discontinuities is demonstrated; this circuit is implemented in complementary metal oxide semiconductor technology.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Harris, J G -- Koch, C -- Luo, J -- New York, N.Y. -- Science. 1990 Jun 8;248(4960):1209-11.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Computation and Neural Systems Program, California Institute of Technology, Pasadena 91125.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/2349479" target="_blank"〉PubMed〈/a〉
Keywords:
Algorithms
;
Computer Graphics
;
*Computer Simulation
;
Humans
;
*Vision, Ocular
Print ISSN:
0036-8075
Electronic ISSN:
1095-9203
Topics:
Biology
,
Chemistry and Pharmacology
,
Computer Science
,
Medicine
,
Natural Sciences in General
,
Physics
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