Why is this Important?
Creating AR experiences using existing authoring environments is a time-consuming process even for highly-trained developers. One of the greatest hurdles is the specification of real world features to which AR assets are attached/anchored. An alternative to manually defining anchors for AR assets is to adapt the outputs of real world 3D capture systems used in enterprises to be used as anchors for AR.
New interfaces and data encodings for 3D capture systems to make those systems directly accessible in an AR authoring pipeline will streamline or automate the preparation of AR experiences based in part on 3D capture of enterprise environments. However, there are many different 3D capture systems. This research topic focuses on development of guidelines and/or standards that will define the formats for 3D real world mapping which can be used by commercial AR authoring platform developers and publishers.
This research is relevant to AR experience developers, AR managers, AR authoring platform publishing companies, AR service providers,
Requirements for this approach for authoring AR experiences will be compared with existing and new standards and/or extensions of existing standards to automate AR authoring. The gaps and requirements will more easily be provided to appropriate standards development organizations for future work. If and when new interfaces and standards are published, enterprise AR authoring software vendors will be able to use these to streamline the AR authoring pipelines in industry.
This topic could be combined with other topics to increase efficiencies in AR asset and experience authoring, management and delivery to reduce time and costs of integration with existing authoring and data management systems and platforms.
This topic was submitted for 8th and 9th AREA research projects and received high support.
3D world capture, depth sensing, liDAR, AR experience authoring, AR assets, anchoring, world mapping, SLAM, simultaneous localization and mapping, standards, data preparation, object-oriented programming, open systems, authoring systems, shape recognition, feature extraction, 3d modeling
Research Agenda Categories
Expected Impact Timeframe
Using the words in this topic description and Natural Language Processing analysis of publications in the AREA FindAR database, the references below have the highest number of matches with this topic:
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