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Title: On-demand transmission model using image-based rendering for remote visualization
Author: Al-Saidi, Asma
ISNI:       0000 0004 2751 9742
Awarding Body: Cardiff University
Current Institution: Cardiff University
Date of Award: 2011
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Interactive distributed visualization is an emerging technology with numerous applications. However, many of the present approaches to interactive distributed visualization have limited performance since they are based on the traditional polygonal processing graphics pipeline. In contrast, image-based rendering uses multiple images of the scene instead of a 3D geometrical representation, and so has the key advantage that the final output is independent of the scene complexity, and depends on the desired final image resolution. These multiple images are referred to as the light field dataset. In this thesis we propose an on-demand solution for efficiently transmitting visualization data to remote users/clients. This is achieved through sending selected parts of the dataset based on the current client viewpoint, and is done instead of downloading a complete replica of the light field dataset to each client, or remotely sending a single rendered view back from a central server to the user each time the user updates their viewing parameters. The on-demand approach shows stable performance as the number of clients increases because the load on the server and the network traffic are reduced. Furthermore, detailed performance studies show that the proposed on-demand scheme outperforms the current local and remote solutions in terms of interactivity measured in frames per second. In addition, a performance study based on a theoretical cost model is presen ted. The model was able to provide realistic estimations of the results for different ranges of dataset sizes. Also, these results indicate that the model can be used as a predictive tool for estimating timings for the visualization process, enabling the improvement of the process and product quality, as well as the further develop ment of models for larger systems and datasets. In further discussing the strengths and weaknesses of each of the models, we see that to be able to run the system for larger dataset resolution involves a trade-off between generality of hardware (the server and network) and dataset resolution. Larger dataset resolution cannot achieve interactive frame rates on current COTS infrastructure. Finally, we conclude that the design of our 3D visualization system, based on image-based rendering coupled with an on-demand transmission model, has made a contribution to the field, and is a good basis for the future development of collaborative, distributed visualization systems.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available