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Proceedings Paper

ToF depth image motion blur detection using 3D blur shape models
Author(s): Seungkyu Lee; Hyunjung Shim; James D. K. Kim; Chang Yeong Kim
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Paper Abstract

Time-of-flight cameras produce 3D geometry enabling faster and easier 3D scene capturing. The depth camera, however, suffers from motion blurs when the movement from either camera or scene appears. Unlike other noises, depth motion blur is hard to eliminate by any general filtering methods and yields the serious distortion in 3D reconstruction, typically causing uneven object boundaries and blurs. In this paper, we provide a through analysis on the ToF depth motion blur and a modeling method which is used to detect a motion blur region from a depth image. We show that the proposed method correctly detects blur regions using the set of all possible motion artifact models.

Paper Details

Date Published: 10 February 2012
PDF: 6 pages
Proc. SPIE 8296, Computational Imaging X, 829615 (10 February 2012); doi: 10.1117/12.908055
Show Author Affiliations
Seungkyu Lee, Samsung Advanced Institute of Technology (Korea, Republic of)
Hyunjung Shim, Samsung Advanced Institute of Technology (Korea, Republic of)
James D. K. Kim, Samsung Advanced Institute of Technology (Korea, Republic of)
Chang Yeong Kim, Samsung Advanced Institute of Technology (Korea, Republic of)


Published in SPIE Proceedings Vol. 8296:
Computational Imaging X
Charles A. Bouman; Ilya Pollak; Patrick J. Wolfe, Editor(s)

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