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.
| Original language | English |
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| Title of host publication | Proceedings of SPIE-IS and T Electronic Imaging - Computational Imaging X |
| DOIs | |
| Publication status | Published - 2012 Mar 13 |
| Event | Computational Imaging X - Burlingame, CA, United States Duration: 2012 Jan 23 → 2012 Jan 24 |
Publication series
| Name | Proceedings of SPIE - The International Society for Optical Engineering |
|---|---|
| Volume | 8296 |
| ISSN (Print) | 0277-786X |
Other
| Other | Computational Imaging X |
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| Country | United States |
| City | Burlingame, CA |
| Period | 12/1/23 → 12/1/24 |
All Science Journal Classification (ASJC) codes
- Electronic, Optical and Magnetic Materials
- Condensed Matter Physics
- Computer Science Applications
- Applied Mathematics
- Electrical and Electronic Engineering
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Cite this
Lee, S., Shim, H., Kim, J. D. K., & Kim, C. Y. (2012). ToF depth image motion blur detection using 3D blur shape models. In Proceedings of SPIE-IS and T Electronic Imaging - Computational Imaging X [829615] (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 8296). https://doi.org/10.1117/12.908055