A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
The complexity of recognizing polyhedral scenes
Journal of Computer and System Sciences - 26th IEEE Conference on Foundations of Computer Science, October 21-23, 1985
Using vanishing points for camera calibration
International Journal of Computer Vision
Parallel algorithms for shared-memory machines
Handbook of theoretical computer science (vol. A)
New method for vanishing point detection
CVGIP: Image Understanding
The Recovery and Understanding of a Line Drawing from Indoor Scenes
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
An introduction to parallel algorithms
An introduction to parallel algorithms
On the complexity of labeling perspective projections of polyhedral scenes
Artificial Intelligence
The complexity of understanding line drawings of Origami scenes
International Journal of Computer Vision
Algorithms for Graphics and Imag
Algorithms for Graphics and Imag
Sketching a virtual environment: modeling using line-drawing interpretation
Proceedings of the ACM symposium on Virtual reality software and technology
Vanishing Point Detection in the Hough Transform Space
Euro-Par '99 Proceedings of the 5th International Euro-Par Conference on Parallel Processing
EM enhancement of 3D head pose estimated by point at infinity
Image and Vision Computing
Physical sketching: Reconstruction and analysis of 3D objects from freehand sketches
Computer-Aided Design
3D video and free viewpoint video-From capture to display
Pattern Recognition
| Hi-index | 0.14 |
This paper investigates the quantitative reconstruction of the 3D structure of a scene from a line drawing, by using the geometrical constraints provided by the location of vanishing points. The additional information on vanishing points allows the design of an algorithm which has several advantages with respect to the usual approach based on a reduction to Linear Programming (Sugihara, 1982). These advantages range from a lower computational complexity to error tolerance and exact reconstruction of the 3D-geometry of the objects. These features make the algorithm a useful tool for the quantitative analysis of real-world images, which is useful for several tasks from scene understanding to automatic vehicle guidance.