Document Detail


Comprehensible visualization for augmented reality.
MedLine Citation:
PMID:  19147885     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
This article presents interactive visualizations to support the comprehension of spatial relationships between virtual and real world objects for Augmented Reality (AR) applications. To enhance the clarity of such relationships we discuss visualization techniques and their suitability for AR. We apply them on different AR applications with different goals, e.g. in X-Ray vision or in applications which draw a user's attention to an object of interest. We demonstrate how Focus and Context (F+C) visualizations are used to affect the user's perception of hidden or nearby objects by presenting contextual information in the area of augmentation. We discuss the organization and the possible sources of data for visualizations in Augmented Reality and present cascaded and multi level F+C visualizations to address complex, cluttered scenes that are inevitable in real environments. This article also shows filters and tools to interactively control the amount of augmentation. It compares the impact of real world context preserving to a pure virtual and uniform enhancement of these structures for augmentations of real world imagery. Finally this paper discusses the stylization of sparse object representations for AR to improve X-Ray vision.
Authors:
Denis Kalkofen; Erick Mendez; Dieter Schmalstieg
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  IEEE transactions on visualization and computer graphics     Volume:  15     ISSN:  1077-2626     ISO Abbreviation:  IEEE Trans Vis Comput Graph     Publication Date:    2009 Mar-Apr
Date Detail:
Created Date:  2009-01-16     Completed Date:  2009-08-10     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9891704     Medline TA:  IEEE Trans Vis Comput Graph     Country:  United States    
Other Details:
Languages:  eng     Pagination:  193-204     Citation Subset:  IM    
Affiliation:
Institute for Computer Graphics and Vision, Graz University of Technology, Graz, Austria. kalkofen@icg.tugraz.at
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MeSH Terms
Descriptor/Qualifier:
Computer Graphics*
Humans
Image Enhancement / methods
Imaging, Three-Dimensional / methods
User-Computer Interface*

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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