Computer Vision for Mobile Augmented Reality View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2015

AUTHORS

Matthew Turk , Victor Fragoso

ABSTRACT

Mobile augmented reality (AR) employs computer vision capabilities in order to properly integrate the real and the virtual, whether that integration involves the user’s location, object-based interaction, 2D or 3D annotations, or precise alignment of image overlays. Real-time vision technologies vital for the AR context include tracking, object and scene recognition, localization, and scene model construction. For mobile AR, which has limited computational resources compared with static computing environments, efficient processing is critical, as are consideration of power consumption (i.e., battery life), processing and memory limitations, lag, and the processing and display requirements of the foreground application. On the other hand, additional sensors (such as gyroscopes, accelerometers, and magnetometers) are typically available in the mobile context, and, unlike many traditional computer vision applications, user interaction is often available for user feedback and disambiguation. In this chapter, we discuss the use of computer vision for mobile augmented reality and present work on a vision-based AR application (mobile sign detection and translation), a vision-supplied AR resource (indoor localization and post estimation), and a low-level correspondence tracking and model estimation approach to increase accuracy and efficiency of computer vision methods in augmented reality. More... »

PAGES

3-42

Book

TITLE

Mobile Cloud Visual Media Computing

ISBN

978-3-319-24700-7
978-3-319-24702-1

From Grant

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-24702-1_1

DOI

http://dx.doi.org/10.1007/978-3-319-24702-1_1

DIMENSIONS

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