Shape from appearance: A statistical approach to surface shape estimation

Darrell R. Hougen, Narendra Ahuja

Research output: Chapter in Book/Report/Conference proceedingConference contribution


This paper is concerned with surface shape estimation by a method in which an empirically determined associative model relating appearance to surface shape is used. Significantly, the estimated model is more accurate than the algorithm that generates the examples. The method presented here is a generalization of shape from shading methods that does not rely upon idealized models of the image formation process. As a relative of shape from shading, this method more accurately recovers small surface detail than is possible with methods such as stereo and motion. The present approach is a continuous analogue of pattern recognition and is closely related to methods of joint space learning used in robotics. Experiments on real scenes are used to illustrate the concepts involved.

Original languageEnglish (US)
Title of host publicationComputer Vision – ECCV 1996 - 4th European Conference on Computer Vision, Proceedings
EditorsBernard Buxton, Roberto Cipolla
Number of pages10
ISBN (Print)3540611223, 9783540611226
StatePublished - 1996
Event4th European Conference on Computer Vision, ECCV 1996 - Cambridge, United Kingdom
Duration: Apr 15 1996Apr 18 1996

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other4th European Conference on Computer Vision, ECCV 1996
Country/TerritoryUnited Kingdom

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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