Linear and incremental acquisition of invariant shape models from image sequences

Daphna Weinshall*, Carlo Tomasi

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

32 Scopus citations

Abstract

We show how to automatically acquire similarity-invariant shape representations of objects from noisy image sequences under weak perspective. The proposed method is linear and incremental, requiring no more than pseudo-inverse. It is based on the observation that the trajectories that points on the object form in weak-perspective image sequences are linear combinations of three of the trajectories themselves, and that the coefficients of the linear combinations represent shape in an affine-invariant basis. A nonlinear but numerically sound preprocessing state is added to improve the accuracy of the results even further. Experiments show that attention to noise and computational techniques improve the shape results substantially with respect to previous methods proposed.

Original languageAmerican English
Title of host publication1993 IEEE 4th International Conference on Computer Vision
PublisherPubl by IEEE
Pages675-682
Number of pages8
ISBN (Print)0818638729
StatePublished - 1993
Externally publishedYes
Event1993 IEEE 4th International Conference on Computer Vision - Berlin, Ger
Duration: 11 May 199314 May 1993

Publication series

Name1993 IEEE 4th International Conference on Computer Vision

Conference

Conference1993 IEEE 4th International Conference on Computer Vision
CityBerlin, Ger
Period11/05/9314/05/93

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