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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Young Min Kim Theobalt, C. Diebel, J. Kosecka, J. Miscusik, B. Thrun, S. |
| Copyright Year | 2009 |
| Description | Author affiliation: Stanford University, USA (Young Min Kim; Theobalt, C.; Diebel, J.; Thrun, S.) || George Mason University, USA (Kosecka, J.; Miscusik, B.) |
| Abstract | Multi-view stereo methods frequently fail to properly reconstruct 3D scene geometry if visible texture is sparse or the scene exhibits difficult self-occlusions. Time-of-Flight (ToF) depth sensors can provide 3D information regardless of texture but with only limited resolution and accuracy. To find an optimal reconstruction, we propose an integrated multi-view sensor fusion approach that combines information from multiple color cameras and multiple ToF depth sensors. First, multi-view ToF sensor measurements are combined to obtain a coarse but complete model. Then, the initial model is refined by means of a probabilistic multi-view fusion framework, optimizing over an energy function that aggregates ToF depth sensor information with multi-view stereo and silhouette constraints. We obtain high quality dense and detailed 3D models of scenes challenging for stereo alone, while simultaneously reducing complex noise of ToF sensors. |
| Starting Page | 1542 |
| Ending Page | 1549 |
| File Size | 1535631 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781424444427 |
| DOI | 10.1109/ICCVW.2009.5457430 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-09-27 |
| Publisher Place | Japan |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Geometry Image sensors Stereo image processing Layout Sensor fusion Sensor phenomena and characterization Cameras Sensor systems Stereo vision Image reconstruction |
| Content Type | Text |
| Resource Type | Article |
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