Citation

Cui J, Ma Z, Popescu V. IEEE Trans. Vis. Comput. Graph. 2013; ePub(ePub): ePub.

Affiliation

Purdue University, West Lafayette.

Copyright

(Copyright © 2013, IEEE (Institute of Electrical and Electronics Engineers))

DOI

477A4A8C-B72E-4BFC-A126-7C14E4CE2F50

PMID

24277948

Abstract

Remote-visualization has become both a necessity, as dataset sizes have grown faster than computer network performance, and an opportunity, as mobile computing platforms have become ubiquitous. However, the conventional remote-visualization approach of sending new images from the server to the client for every view-parameter change suffers from reduced interactivity. One problem is high latency, as the network has to be traversed twice for each interaction of client with server. A second problem is reduced image quality due to aggressive compression or reduced resolution. We address these problems by constructing and transmitting enhanced images that are sufficient for quality output frame reconstruction at the client for a range of view-parameter values. The client reconstructs thousands of frames locally, without any additional data from the server, which avoids latency and aggressive compression. We introduce animated depth images, which not only store a color and depth sample at every pixel, but also store the trajectory of the samples for a given time interval. Sample trajectories are stored compactly by partitioning the image into semi-rigid sample clusters and by storing one sequence of rigid body transformations per cluster. Animated depth images leverage sample trajectory coherence to achieve a good compression of animation data, with a small and user-controllable approximation error.

Language: en