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Abstract In‐field visual inspections have inherent challenges associated with humans such as low accuracy, excessive cost and time, and safety. To overcome these barriers, researchers and industry leaders have developed image‐based methods for automatic structural crack detection. More recently, researchers have proposed using augmented reality (AR) to interface human visual inspection with automatic image‐based crack detection. However, to date, AR crack detection is limited because: (1) it is not available in real time and (2) it requires an external processing device. This paper describes a new AR methodology that addresses both problems enabling a standalone real‐time crack detection system for field inspection. A Canny algorithm is transformed into the single‐dimensional mathematical environment of the AR headset digital platform. Then, the algorithm is simplified based on the limited headset processing capacity toward lower processing time. The test of the AR crack‐detection method eliminates AR image‐processing dependence on external processors and has practical real‐time image‐processing.
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ARtisan Bistro: A Cooking Task Environment to Conduct Studies in Augmented Reality
With the increasing popularity of Augmented Reality (AR) and newer emerging technologies for normal consumers there is an in- creasing need to research AR applications in more general everyday settings. ARtisan Bistro is an attempt to create a base layer environment that other researchers can build on. Our effort is to save researchers the time of developing an environment from scratch and focus more on the core part of their research.
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- Award ID(s):
- 2016714
- PAR ID:
- 10366099
- Date Published:
- Journal Name:
- IEEE International Symposium on Mixed and Augmented Reality Adjunct ISMARAdjunct
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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