A Method for Enforcing Integrability in Shape from Shading Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Surface Orientation from a Projected Grid
IEEE Transactions on Pattern Analysis and Machine Intelligence
Height and gradient from shading
International Journal of Computer Vision
SUSAN—A New Approach to Low Level Image Processing
International Journal of Computer Vision
Stereo Matching with Nonlinear Diffusion
International Journal of Computer Vision
Direct Estimation of Shape from Texture
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape from Single Stripe Pattern Illumination
Proceedings of the 24th DAGM Symposium on Pattern Recognition
Surface Reconstruction from Feature Based Stereo
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
A Similarity-Based Aspect-Graph Approach to 3D Object Recognition
International Journal of Computer Vision
Three-Dimensional Face Recognition
International Journal of Computer Vision
3D Feature Tracking Using a Dynamic Structured Light System
CRV '05 Proceedings of the 2nd Canadian conference on Computer and Robot Vision
3D acquisition system using uncalibrated line-laser projec
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 01
Dense Stereo Range Sensing with Marching Pseudo-Random Patterns
CRV '07 Proceedings of the Fourth Canadian Conference on Computer and Robot Vision
Registration of 3D Points Using Geometric Algebra and Tensor Voting
International Journal of Computer Vision
Shape from shading using graph cuts
Pattern Recognition
Optimised De Bruijn patterns for one-shot shape acquisition
Image and Vision Computing
Towards a real-time 3D shape reconstruction using a structured light system
Pattern Recognition
Determining Both Surface Position and Orientation in Structured-Light-Based Sensing
IEEE Transactions on Pattern Analysis and Machine Intelligence
Vision Processing for Realtime 3-D Data Acquisition Based on Coded Structured Light
IEEE Transactions on Image Processing
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Structured light-based sensing (SLS) requires the illumination to be coded either spatially or temporally in the illuminated pattern. However, while the former demands the use of uniquely coded spatial windows whose size grows with the reconstruction resolution and thereby demanding increasing smoothness on the imaged scene, the latter demands the use of multiple image captures. This article presents how the illumination of a very simple pattern plus a single image capture can also achieve 3D reconstruction. The illumination and imaging setting has the configuration of a typical SLS system, comprising a projector and a camera. The difference is, the illumination is not much more than a checkerboard-like pattern - a non-structured pattern in the language of SLS - that does not provide direct correspondence between the camera's image plane and the projector's display panel. The system works from the image progressively, first constructing the orientation map of the target object from the observed grid-lines, then inferring the depth map by the use of a few tricks related to interpolation. The system trades off little accuracy of the traditional SLSs with simplicity of its operation. Compared to temporally coded SLSs, the system has the essence that it requires only one image capture to operate; compared with spatially coded SLSs, it requires no use of spatial windows, and in turn a less degree of smoothness on the object surface; compared with methods like shape from shading and photometric stereo, owing to the use of artificial illumination it is less affected by the surface reflectance property of the target surface and the ambient lighting condition.