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Proceedings Paper

Unsupervised object segmentation for 2D to 3D conversion
Author(s): Matthias Kunter; Sebastian Knorr; Andreas Krutz; Thomas Sikora
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Paper Abstract

In this paper, we address the handling of independently moving objects (IMOs) in automatic 2D to stereoscopic 3D conversion systems based on structure-from-motion (SfM) techniques. Exploiting the different viewing positions of a moving camera, these techniques yield excellent 3D results for static scene objects. However, the independent motion of any foreground object requires a separate conversion process. We propose a novel segmentation approach that estimates the occluded static background and segments the IMOs based on advanced change detection. The background estimation is achieved applying 2D registration and blending techniques, representing an approximation of the underlying scene geometry. The segmentation process itself uses anisotropic filtering applied on the difference image between original frame and the estimated background frame. In order to render the segmented objects into the automatically generated 3D scene properly, a small amount of user interaction will be necessary, e.g. an assignment of intra-object depth or the object's absolute z-position. Experiments show that the segmentation method achieves accurate mask results for a variety of scenes, similar to the masks obtained manually using state-of-the-art rotoscoping tools. Though, this work contributes to the extension of SfM-based automatic 3D conversion methods for the application on dynamic scenes.

Paper Details

Date Published: 18 February 2009
PDF: 10 pages
Proc. SPIE 7237, Stereoscopic Displays and Applications XX, 72371B (18 February 2009); doi: 10.1117/12.806237
Show Author Affiliations
Matthias Kunter, imcube, Technische Univ. Berlin (Germany)
Sebastian Knorr, imcube, Technische Univ. Berlin (Germany)
Andreas Krutz, Technische Univ. Berlin (Germany)
Thomas Sikora, Technische Univ. Berlin (Germany)

Published in SPIE Proceedings Vol. 7237:
Stereoscopic Displays and Applications XX
Andrew J. Woods; Nicolas S. Holliman; John O. Merritt, Editor(s)

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