Presentation
Comparison of Natural Feature Descriptors for Rigid-Object Tracking for Real-Time Augmented Reality
Proceedings of the ASME 2014 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference
Document Type
Conference Proceeding
Disciplines
Conference
ASME 2014 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference
Publication Version
Published Version
Publication Date
1-1-2014
Conference Title
IDETC/CIE 2014
Conference Date
2014
Geolocation
(42.88644679999999, -78.8783689)
Abstract
This paper presents a comparison of natural feature descrip- tors for rigid object tracking for augmented reality (AR) applica- tions. AR relies on object tracking in order to identify a physical object and to superimpose virtual object on an object. Natu- ral feature tracking (NFT) is one approach for computer vision- based object tracking. NFT utilizes interest points of a physcial object, represents them as descriptors, and matches the descrip- tors against reference descriptors in order to identify a phsical object to track. In this research, we investigate four different nat- ural feature descriptors (SIFT, SURF, FREAK, ORB) and their capability to track rigid objects. Rigid objects need robust de- scriptors since they need to describe the objects in a 3D space. AR applications are also real-time application, thus, fast feature matching is mandatory. FREAK and ORB are binary descriptors, which promise a higher performance in comparison to SIFT and SURF. We deployed a test in which we match feature descriptors to artificial rigid objects. The results indicate that the SIFT de- scriptor is the most promising solution in our addressed domain, AR-based assembly training.
Copyright Owner
ASME
Copyright Date
2014
Language
en
File Format
application/pdf
Citation Information
France Franco Bermudez, Sheneeka Ward, Christian Santana Diaz, Rafael Radkowski, et al.. "Comparison of Natural Feature Descriptors for Rigid-Object Tracking for Real-Time Augmented Reality" Buffalo, NYProceedings of the ASME 2014 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference (2014) Available at: http://works.bepress.com/james_oliver/56/
This proceeding is published as Bermudez, Francely Franco, Christian Santana Diaz, Sheneeka Ward, Rafael Radkowski, Timothy Garrett, and James Oliver. "Comparison of Natural Feature Descriptors for Rigid-Object Tracking for Real-Time Augmented Reality." In ASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, pp. V01BT02A044-V01BT02A044. American Society of Mechanical Engineers, 2014. Posted with permission.