Readings in computer vision: issues, problems, principles, and paradigms
Randomized Hough transform (RHT): basic mechanisms, algorithms, and computational complexities
CVGIP: Image Understanding
Use of the Hough transformation to detect lines and curves in pictures
Communications of the ACM
A new randomized algorithm for detecting lines
Real-Time Imaging
Comparisons of Probabilistic and Non-probabilistic Hough Transforms
ECCV '94 Proceedings of the Third European Conference-Volume II on Computer Vision - Volume II
Matching with PROSAC " Progressive Sample Consensus
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
N-Point Hough transform for line detection
Journal of Visual Communication and Image Representation
Fast detection of arbitrary planar surfaces from unreliable 3D data
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
3D dense reconstruction from 2D video sequence via 3D geometric segmentation
Journal of Visual Communication and Image Representation
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This paper deals with shape extraction from depth images (point clouds) in the context of modern robotic vision systems. It presents various optimizations of the 3D Hough Transform used for plane extraction from point cloud data. Presented enhancements of standard methods address problems related to noisy data, high memory requirements for the parameter space and computational complexity of point accumulations. The realised robust plane detector benefits from a continuous point cloud stream generated by a depth sensor over time. It is used for iterative refinements of the results. The system is compared to a state-of-the-art RANSAC-based plane detector from the Point Cloud Library (PCL). Experimental results show that it overcomes the PCL alternative in the stability of plane detection and in the number of negative detections. This advantage is crucial for robotic applications, e.g., when a robot approaches a wall, it can be consistently recognized. The paper concludes with a discussion of further promising optimisation that will be implemented as a future step.