Line-Based Structure from Motion for Urban Environments
We present a novel method for recovering the 3D-line structure of a scene from multiple widely separated views. Traditional optimization-based approaches to line-based structure from motion minimize the error between measured line segments and the projections of corresponding 3D lines. In such a cas...
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| Vydáno v: | 3DPVT 2006 : Third International Symposium on 3D Data Processing, Visualization, and Transmission : June 14-16, 2006, University of North Carolina, Chapel Hill, USA s. 846 - 853 |
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| Hlavní autoři: | , , |
| Médium: | Konferenční příspěvek |
| Jazyk: | angličtina japonština |
| Vydáno: |
IEEE
01.06.2006
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| ISBN: | 0769528252, 9780769528250 |
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| Abstract | We present a novel method for recovering the 3D-line structure of a scene from multiple widely separated views. Traditional optimization-based approaches to line-based structure from motion minimize the error between measured line segments and the projections of corresponding 3D lines. In such a case, 3D lines can be optimized using a minimum of 4 parameters. We show that this number of parameters can be further reduced by introducing additional constraints on the orientations of lines in a 3D scene. In our approach, 2D-lines are automatically detected in images with the assistance of an EM-based vanishing point estimation method which assumes the existence of edges along mutally orthogonal vanishing directions. Each detected line is automatically labeled with the orientation (e.g. vertical, horizontal) of the 3D line which generated the measurement, and it is this additional knowledge that we use to reduce the number of degrees of freedom of 3D lines during optimization. We present 3D reconstruction results for urban scenes based on manually established feature correspondences across images. |
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| AbstractList | We present a novel method for recovering the 3D-line structure of a scene from multiple widely separated views. Traditional optimization-based approaches to line-based structure from motion minimize the error between measured line segments and the projections of corresponding 3D lines. In such a case, 3D lines can be optimized using a minimum of 4 parameters. We show that this number of parameters can be further reduced by introducing additional constraints on the orientations of lines in a 3D scene. In our approach, 2D-lines are automatically detected in images with the assistance of an EM-based vanishing point estimation method which assumes the existence of edges along mutally orthogonal vanishing directions. Each detected line is automatically labeled with the orientation (e.g. vertical, horizontal) of the 3D line which generated the measurement, and it is this additional knowledge that we use to reduce the number of degrees of freedom of 3D lines during optimization. We present 3D reconstruction results for urban scenes based on manually established feature correspondences across images. |
| Author | Schindler, G. Krishnamurthy, P. Dellaert, F. |
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| PublicationTitle | 3DPVT 2006 : Third International Symposium on 3D Data Processing, Visualization, and Transmission : June 14-16, 2006, University of North Carolina, Chapel Hill, USA |
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| Snippet | We present a novel method for recovering the 3D-line structure of a scene from multiple widely separated views. Traditional optimization-based approaches to... |
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| SubjectTerms | Image edge detection Image reconstruction Layout Motion measurement |
| Title | Line-Based Structure from Motion for Urban Environments |
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