Tour into the picture: using a spidery mesh interface to make animation from a single image
Proceedings of the 24th annual conference on Computer graphics and interactive techniques
Metric Rectification for Perspective Images of Planes
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Scene Modeling Based on Constraint System Decomposition Techniques
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
3DIM '05 Proceedings of the Fifth International Conference on 3-D Digital Imaging and Modeling
Self-Calibration of Multiple Laser Planes for 3D Scene Reconstruction
3DPVT '06 Proceedings of the Third International Symposium on 3D Data Processing, Visualization, and Transmission (3DPVT'06)
Dense 3D Reconstruction method using Coplanarities and Metric Constraints for Line Laser Scanning
3DIM '07 Proceedings of the Sixth International Conference on 3-D Digital Imaging and Modeling
A low-cost range finder using a visually located, structured light source
3DIM'99 Proceedings of the 2nd international conference on 3-D digital imaging and modeling
Calibration of double stripe 3D laser scanner systems using planarity and orthogonality constraints
Digital Signal Processing
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In this paper, we propose a novel method to achieve both dense 3D reconstruction of the scene and estimation of the camera intrinsic parameters by using coplanarities and other constraints (e.g., orthogonalities or parallelisms) derived from relations between planes in the scene and reflected curves of line lasers captured by a single camera. In our study, we categorize coplanarities in the scene into two types: implicit coplanarities, which can be observed as reflected curves of line lasers, and explicit coplanarities, which are, for example, observed as walls of a building. By using both types of coplanarities, we can construct simultaneous equations and can solve them up to four degrees of freedom. To upgrade the solution to the Euclidean space and estimate the camera intrinsic parameters, we can use metric constraints such as orthogonalities of the planes. Such metric constraints are given by, for example, observing the corners of rectangular boxes in the scene, or using special laser projecting device composed of two line lasers whose laser planes are configured to be perpendicular.