COMPUTER VISION METHODS RESEARCH AND APPLICATION IN AUGMENTED REALITY SYSTEMS
Journal Title: Jaunųjų mokslininkų darbai - Year 2014, Vol 41, Issue 1
Abstract
Augmented reality is a widely used visualization technique in various application fields which usually tracks artificial objects, for instance, markers that let users add 3D virtual content into the real world. The main problem with using markers is the occlusions from users or objects in the environment. These occlusions usually cause virtual content to disappear; therefore, it has negative impact to the usability of the application. For this reason the analysis of computer vision methods FAST (Feature from Accelerated Segment Test), SIFT (Scale Invariant Feature Transform) and SURF (Speeded Up Robust Features) are presented that can solve partial occlusion problems. Robustness comparison was based on a repeatability criteria using different types of image transformation sets. Speed and suitability of computer vision methods were also evaluated for augmented reality technology. The research results are essential in order to select the proper computer vision technique for augmented reality solutions and further improvements.
Authors and Affiliations
Edgaras Artemčiukas, Leonidas Sakalauskas
Keywords
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