Openly accessible

Emerging hypothesis verification using function-based geometric models and active vision strategies

Lam, C. P., West, G. A. W. and Venkatesh, S. 1994, Emerging hypothesis verification using function-based geometric models and active vision strategies, in CVPR'94 : Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, IEEE, Los Alamitos, Calif., pp. 818-822.

Attached Files
Name Description MIMEType Size Downloads
venkatesh-emerginghypothesis-1994.pdf Published version application/pdf 442.17KB 45

Title Emerging hypothesis verification using function-based geometric models and active vision strategies
Author(s) Lam, C. P.
West, G. A. W.
Venkatesh, S.
Conference name IEEE Computer Society Conference on Computer Vision and Pattern Recognition (1994 : Seattle, Wash.)
Conference location Seattle, Wash.
Conference dates 21-23 Jun. 1994
Title of proceedings CVPR'94 : Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Editor(s) [Unknown]
Publication date 1994
Conference series IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Start page 818
End page 822
Total pages 5
Publisher IEEE
Place of publication Los Alamitos, Calif.
Keyword(s) machine vision
object recognition
computer vision
3D shape
active vision
correspondence
edge points
foveation
function-based geometric models
hypothesis verification
kinematic model
parametric 2D models
Summary This paper describes an investigation into the use of parametric 2D models describing the movement of edges for the determination of possible 3D shape and hence function of an object. An assumption of this research is that the camera can foveate and track particular features. It is argued that simple 2D analytic descriptions of the movement of edges can infer 3D shape while the camera is moved. This uses an advantage of foveation i.e. the problem becomes object centred. The problem of correspondence for numerous edge points is overcome by the use of a tree based representation for the competing hypotheses. Numerous hypothesis are maintained simultaneously and it does not rely on a single kinematic model which assumes constant velocity or acceleration. The numerous advantages of this strategy are described.
Notes This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
ISBN 0818658274
ISSN 1063-6919
Language eng
Field of Research 089999 Information and Computing Sciences not elsewhere classified
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category E1.1 Full written paper - refereed
Copyright notice ©1994, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30044556

Document type: Conference Paper
Collections: School of Information Technology
Open Access Collection
Connect to link resolver
 
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.

Versions
Version Filter Type
Citation counts: Scopus Citation Count Cited 2 times in Scopus
Google Scholar Search Google Scholar
Access Statistics: 36 Abstract Views, 45 File Downloads  -  Detailed Statistics
Created: Fri, 20 Apr 2012, 11:32:01 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.