21 May 2004 Temporally consistent virtual camera generation from stereo image sequences
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Abstract
The recent emergence of auto-stereoscopic 3D viewing technologies has increased demand for the creation of 3D video content. A range of glasses-free multi-viewer screens have been developed that require as many as 9 views generated for each frame of video. This presents difficulties in both view generation and transmission bandwidth. This paper examines the use of stereo video capture as a means to generate multiple scene views via disparity analysis. A machine learning approach is applied to learn relationships between disparity generated depth information and source footage, and to generate depth information in a temporally smooth manner for both left and right eye image sequences. A view morphing approach to multiple view rendering is described which provides an excellent 3D effect on a range of glasses-free displays, while providing robustness to inaccurate stereo disparity calculations.
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Simon R. Fox, Simon R. Fox, Julien Flack, Julien Flack, Juliang Shao, Juliang Shao, Phil Harman, Phil Harman, } "Temporally consistent virtual camera generation from stereo image sequences", Proc. SPIE 5291, Stereoscopic Displays and Virtual Reality Systems XI, (21 May 2004); doi: 10.1117/12.527895; https://doi.org/10.1117/12.527895
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