Comparison of Natural Feature Descriptors for Rigid-Object Tracking for Real-Time Augmented Reality

Thumbnail Image
Date
2014-01-01
Authors
Bermudez, France
Ward, Sheneeka
Diaz, Christian
Radkowski, Rafael
Garrett, Timothy
Major Professor
Advisor
Committee Member
Journal Title
Journal ISSN
Volume Title
Publisher
Authors
Person
Oliver, James
Director-SICTR
Research Projects
Organizational Units
Organizational Unit
Mechanical Engineering
The Department of Mechanical Engineering at Iowa State University is where innovation thrives and the impossible is made possible. This is where your passion for problem-solving and hands-on learning can make a real difference in our world. Whether you’re helping improve the environment, creating safer automobiles, or advancing medical technologies, and athletic performance, the Department of Mechanical Engineering gives you the tools and talent to blaze your own trail to an amazing career.
Organizational Unit
Virtual Reality Applications Center
At VRAC, our mission is clear: “To elevate the synergy between humans and complex interdisciplinary systems to unprecedented levels of performance”. Through our exceptional Human Computer Interaction (HCI) graduate program, we nurture the next generation of visionaries and leaders in the field, providing them with a comprehensive understanding of the intricate relationship between humans and technology. This empowers our students to create intuitive and transformative user experiences that bridge the gap between innovation and practical application.
Organizational Unit
Electrical and Computer Engineering

The Department of Electrical and Computer Engineering (ECpE) contains two focuses. The focus on Electrical Engineering teaches students in the fields of control systems, electromagnetics and non-destructive evaluation, microelectronics, electric power & energy systems, and the like. The Computer Engineering focus teaches in the fields of software systems, embedded systems, networking, information security, computer architecture, etc.

History
The Department of Electrical Engineering was formed in 1909 from the division of the Department of Physics and Electrical Engineering. In 1985 its name changed to Department of Electrical Engineering and Computer Engineering. In 1995 it became the Department of Electrical and Computer Engineering.

Dates of Existence
1909-present

Historical Names

  • Department of Electrical Engineering (1909-1985)
  • Department of Electrical Engineering and Computer Engineering (1985-1995)

Related Units

Organizational Unit
Materials Science and Engineering

The Department of Materials Science and Engineering teaches the composition, microstructure, and processing of materials as well as their properties, uses, and performance. These fields of research utilize technologies in metals, ceramics, polymers, composites, and electronic materials.

History
The Department of Materials Science and Engineering was formed in 1975 from the merger of the Department of Ceramics Engineering and the Department of Metallurgical Engineering.

Dates of Existence
1975-present

Related Units

Journal Issue
Is Version Of
Versions
Series
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.

Comments

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.

Description
Keywords
Citation
DOI
Source
Copyright
Wed Jan 01 00:00:00 UTC 2014