Abstract
We present a novel fusion method that combines complementary 3D and 2D imaging techniques. Consider a Time-of-Flight sensor that acquires a dense depth map on a wide depth range but with a comparably small resolution. Complementary, a stereo sensor generates a disparity map in high resolution but with occlusions and outliers. In our method, we fuse depth data, and optionally also intensity data using a primal-dual optimization, with an energy functional that is designed to compensate for missing parts, filter strong outliers and reduce the acquisition noise. The numerical algorithm is efficiently implemented on a GPU to achieve a processing speed of 10 to 15 frames per second. Experiments on synthetic, real and benchmark datasets show that the results are superior compared to each sensor alone and to competing optimization techniques. In a practical example, we are able to fuse a Kinect triangulation sensor and a small size Time-of-Flight camera to create a gaming sensor with superior resolution, acquisition range and accuracy
Original language | English |
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Title of host publication | Computational Photography (ICCP), 2013 IEEE International Conference on |
Pages | 1-8 |
DOIs | |
Publication status | Published - 2013 |
Event | 2013 IEEE International Conference on Computational Photography : ICCP 2013 - Cambridge, United States Duration: 19 Apr 2013 → 21 Apr 2013 |
Conference
Conference | 2013 IEEE International Conference on Computational Photography |
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Abbreviated title | ICCP 2013 |
Country/Territory | United States |
City | Cambridge |
Period | 19/04/13 → 21/04/13 |
Fields of Expertise
- Information, Communication & Computing
Treatment code (Nähere Zuordnung)
- Basic - Fundamental (Grundlagenforschung)
- Review
- Popular Scientific