A new curve detection method: randomized Hough transform (RHT)
Pattern Recognition Letters
Model-based and learned semantic object labeling in 3D point cloud maps of kitchen environments
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Efficient multi-resolution plane segmentation of 3d point clouds
ICIRA'11 Proceedings of the 4th international conference on Intelligent Robotics and Applications - Volume Part II
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The processing of point clouds for extracting semantic knowledge plays a crucial role in state of the art mobile robot applications. In this work, we examine plane extraction methods that do not rely on additional point features such as normals, but rather on random triangulation in order to allow for a fast segmentation. When it comes to an implementation in this context, typically the following question arises: RANSAC or Hough transform? In this paper, we examine both methods and propose a novel plane extraction approach based on the randomized 3D Hough transform. Our main concerns for improvement are extraction time, accuracy, robustness as well as memory consumption.