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
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
ACM SIGGRAPH 2005 Papers
Geometric Context from a Single Image
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
A Dynamic Bayesian Network Model for Autonomous 3D Reconstruction from a Single Indoor Image
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Fast Automatic Single-View 3-d Reconstruction of Urban Scenes
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part II
Make3D: Learning 3D Scene Structure from a Single Still Image
IEEE Transactions on Pattern Analysis and Machine Intelligence
LSD: A Fast Line Segment Detector with a False Detection Control
IEEE Transactions on Pattern Analysis and Machine Intelligence
Geometric image parsing in man-made environments
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part II
TILT: transform invariant low-rank textures
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part III
Hi-index | 0.00 |
This paper deals with automatic Single View Reconstruction (SVR) of multi-planar scenes characterized by a profusion of straight lines and mutually orthogonal line-pairs. We provide a new shape-from-X constraint based on this regularity of angles between line-pairs in man-made scenes. First, we show how the presence of such regular angles can be used for 2D rectification of an image of a plane. Further, we propose an automatic SVR method assuming there are enough orthogonal line-pairs available on each plane. This angle regularity is only imposed on physically intersecting line-pairs, making it a local constraint. Unlike earlier literature, our approach does not make restrictive assumptions about the orientation of the planes or the camera and works for both indoor and outdoor scenes. Results are shown on challenging images which would be difficult to reconstruct for existing automatic SVR algorithms.