A survey of the Hough transform
Computer Vision, Graphics, and Image Processing
A new curve detection method: randomized Hough transform (RHT)
Pattern Recognition Letters
Performance Evaluation and Analysis of Vanishing Point Detection Techniques
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Flexible New Technique for Camera Calibration
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiple view geometry in computer vision
Multiple view geometry in computer vision
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
The Cascaded Hough Transform as Support for Grouping and Finding Vanishing Points and Lines
AFPAC '97 Proceedings of the International Workshop on Algebraic Frames for the Perception-Action Cycle
On the Discretization of Parameter Domain in Hough Transformation
ICPR '96 Proceedings of the 13th International Conference on Pattern Recognition - Volume 2
Robust Multiple Structures Estimation with J-Linkage
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
Depth Imaging by Combining Time-of-Flight and On-Demand Stereo
Dyn3D '09 Proceedings of the DAGM 2009 Workshop on Dynamic 3D Imaging
MixIn3D: 3D Mixed Reality with ToF-Camera
Dyn3D '09 Proceedings of the DAGM 2009 Workshop on Dynamic 3D Imaging
Interpreting perspective images
Artificial Intelligence
Time-of-Flight sensor calibration for accurate range sensing
Computer Vision and Image Understanding
Robust radial distortion from a single image
ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part II
Projective alignment of range and parallax data
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
A Global Approach for the Detection of Vanishing Points and Mutually Orthogonal Vanishing Directions
CVPR '13 Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition
Unsupervised Intrinsic Calibration from a Single Frame Using a "Plumb-Line" Approach
ICCV '13 Proceedings of the 2013 IEEE International Conference on Computer Vision
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It is convenient to calibrate time-of-flight cameras by established methods, using images of a chequerboard pattern. The low resolution of the amplitude image, however, makes it difficult to detect the board reliably. Heuristic detection methods, based on connected image-components, perform very poorly on this data. An alternative, geometrically-principled method is introduced here, based on the Hough transform. The projection of a chequerboard is represented by two pencils of lines, which are identified as oriented clusters in the gradient-data of the image. A projective Hough transform is applied to each of the two clusters, in axis-aligned coordinates. The range of each transform is properly bounded, because the corresponding gradient vectors are approximately parallel. Each of the two transforms contains a series of collinear peaks; one for every line in the given pencil. This pattern is easily detected, by sweeping a dual line through the transform. The proposed Hough-based method is compared to the standard OpenCV detection routine, by application to several hundred time-of-flight images. It is shown that the new method detects significantly more calibration boards, over a greater variety of poses, without any overall loss of accuracy. This conclusion is based on an analysis of both geometric and photometric error.