MIT Libraries homeMIT Libraries logoDSpace@MIT

MIT
View Item 
  • DSpace@MIT Home
  • Computer Science and Artificial Intelligence Lab (CSAIL)
  • Artificial Intelligence Lab Publications
  • AI Memos (1959 - 2004)
  • View Item
  • DSpace@MIT Home
  • Computer Science and Artificial Intelligence Lab (CSAIL)
  • Artificial Intelligence Lab Publications
  • AI Memos (1959 - 2004)
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Analog "Neuronal" Networks in Early Vision

Author(s)
Koch, Christof; Marroquin, Jose; Yuille, Alan
Thumbnail
DownloadAIM-751.ps (3.120Mb)
Additional downloads
AIM-751.pdf (2.430Mb)
Metadata
Show full item record
Abstract
Many problems in early vision can be formulated in terms of minimizing an energy or cost function. Examples are shape-from-shading, edge detection, motion analysis, structure from motion and surface interpolation (Poggio, Torre and Koch, 1985). It has been shown that all quadratic variational problems, an important subset of early vision tasks, can be "solved" by linear, analog electrical or chemical networks (Poggio and Koch, 1985). IN a variety of situateions the cost function is non-quadratic, however, for instance in the presence of discontinuities. The use of non-quadratic cost functions raises the question of designing efficient algorithms for computing the optimal solution. Recently, Hopfield and Tank (1985) have shown that networks of nonlinear analog "neurons" can be effective in computing the solution of optimization problems. In this paper, we show how these networks can be generalized to solve the non-convex energy functionals of early vision. We illustrate this approach by implementing a specific network solving the problem of reconstructing a smooth surface while preserving its discontinuities from sparsely sampled data (Geman and Geman, 1984; Marroquin 1984; Terzopoulos 1984). These results suggest a novel computational strategy for solving such problems for both biological and artificial vision systems.
Date issued
1985-06-01
URI
http://hdl.handle.net/1721.1/5654
Other identifiers
AIM-751
Series/Report no.
AIM-751
Keywords
analog networks, analog-digital hardware, parallel computers, ssurface interpolation, surface reconstruction, optimization problem, sregularization theory, early vision

Collections
  • AI Memos (1959 - 2004)

Browse

All of DSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

My Account

Login

Statistics

OA StatisticsStatistics by CountryStatistics by Department
MIT Libraries homeMIT Libraries logo

Find us on

Twitter Facebook Instagram YouTube RSS

MIT Libraries navigation

SearchHours & locationsBorrow & requestResearch supportAbout us
PrivacyPermissionsAccessibility
MIT
Massachusetts Institute of Technology
Content created by the MIT Libraries, CC BY-NC unless otherwise noted. Notify us about copyright concerns.