Rapid interactive modelling and tracking for mixed and augmented reality.
Doctoral thesis, UCL (University College London).
We present a novel approach to mixed reality setup and configuration that is rapid, interactive, live, and video-based. Where the operator is directly involved in a responsive modelling process and can specify, define and semantically label the reconstruction. By using commonly available hardware and making minimal demands on the operator’s skill, our approach makes mixed reality more accessible for wider application. Some tasks vital to a mixed reality system are either too time consuming or too complex to be carried out whilst the system is active. 3-dimensional scene modelling, specification and registration are such tasks, commonly performed by skilled operators in an off-line initialisation phase prior to system activation. In this thesis we propose a new on-line interactive method, where a creative video-based modelling process is performed during the run-time phase of operation. Using primitive shape-based modelling techniques, traditionally applied to still photographic image reconstruction, we demonstrate how extrinsic camera calibration, scene reconstruction, specification and registration can be effectively achieved whilst a mixed reality system is active. The two steps required to realise manual on-line video-based modelling are described in this thesis. The first step shows how such modelling techniques can be applied to live video. The second step shows how freely moving cameras can be used to support the modelling processes by combining tracking techniques into a single application. To estimate the potential reconstruction accuracy for both steps a series of tests are performed. Underlying our video-based modelling approach, we present two new algorithms for translating 2-dimensional user interactions into well specified 3-dimensional geometric models, as well as a new approach to combined modelling and tracking that utilises both markers and appearance based tracking techniques in a single solution. Finally, we present a new algorithm for estimating tracking error in real-time, which we use to aid our modelling processes and support our accuracy testing.
|Title:||Rapid interactive modelling and tracking for mixed and augmented reality|
|Additional information:||Permission for digitisation not received|
|UCL classification:||UCL > School of BEAMS > Faculty of Engineering Science > Computer Science|
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