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Proceedings Paper

Converting conventional stereo pairs to multiview sequences using morphing
Author(s): Roger Olsson; Vamsi Kiran Adhikarla; Sebastian Schwarz; Mårten Sjöström
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Paper Abstract

Autostereoscopic multi view displays require multiple views of a scene to provide motion parallax. When an observer changes viewing angle different stereoscopic pairs are perceived. This allows new perspectives of the scene to be seen giving a more realistic 3D experience. However, capturing arbitrary number of views is at best cumbersome, and in some occasions impossible. Conventional stereo video (CSV) operates on two video signals captured using two cameras at two different perspectives. Generation and transmission of two views is more feasible than that of multiple views. It would be more efficient if multiple views required by an autostereoscopic display can be synthesized from these sparse set of views. This paper addresses the conversion of stereoscopic video to multiview video using the video effect morphing. Different morphing algorithms are implemented and evaluated. Contrary to traditional conversion methods, these algorithms disregard the physical depth explicitly and instead generate intermediate views using sparse sets of correspondence features and image morphing. A novel morphing algorithm is also presented that uses scale invariant feature transform (SIFT) and segmentation to construct robust correspondences features and qualitative intermediate views. All algorithms are evaluated on a subjective and objective basis and the comparison results are presented.

Paper Details

Date Published: 27 February 2012
PDF: 8 pages
Proc. SPIE 8288, Stereoscopic Displays and Applications XXIII, 828828 (27 February 2012); doi: 10.1117/12.909253
Show Author Affiliations
Roger Olsson, Mid Sweden Univ. (Sweden)
Vamsi Kiran Adhikarla, Blekinge Institute of Technology (Sweden)
Sebastian Schwarz, Mid Sweden Univ. (Sweden)
Mårten Sjöström, Mid Sweden Univ. (Sweden)

Published in SPIE Proceedings Vol. 8288:
Stereoscopic Displays and Applications XXIII
Andrew J. Woods; Nicolas S. Holliman; Gregg E. Favalora, Editor(s)

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