Abstract
We introduce a fast, robust and accurate Hough Transform (HT) based algorithm for detecting spherical structures in 3D point clouds. To our knowledge, our algorithm is the first HT based implementation that detects spherical structures in typical in 3D point clouds generated by consumer depth sensors such as the Microsoft Kinect. Our approach has been designed to be computationally efficient; reducing an established limitation of HT based approaches. We provide experimental analysis of the achieved results, showing a robust performance against occlusion, and we show superior performance to the only other HT based algorithm for detecting spheres in point clouds available in literature.
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References
Hough, P.: Method and Means for Recognizing Complex Patterns. U.S. Patent 3.069.654 (1962)
Rusu, R.B.: Semantic 3D Object Maps for Everyday Manipulation in Human Living Environments. PhD thesis, Computer Science department, Technische Universitat Munchen, Germany (2009)
Fischler, M.A., Bolles, R.C.: Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography. Communications of the ACM 24(6), 381–395 (1981)
Schnabel, R., Wahl, R., Klein, R.: Efficient RANSAC for Point-Cloud Shape Detection. Computer Graphics Forum 26(2), 214–226 (2007)
Borrmann, D., Elseberg, J., Lingemann, K., Nüchter, A.: The 3D Hough Transform for plane detection in point clouds: A review and a new accumulator design. 3D Research 2(2), 1–13 (2011)
Ogundana, O.O., Coggrave, C.R., Burguete, R.L., Huntley, J.M.: Automated detection of planes in 3-D point clouds using fast Hough transforms. Optical Engineering 50(5), 053609–053609 (2011)
Ogundana, O.O., Coggrave, C.R., Burguete, R.L., Huntley, J.M.: Fast Hough transform for automated detection of spheres in three-dimensional point clouds. Optical Engineering 46(5), 051002–051002 (2007)
Cao, M.Y., Ye, C.H., Doessel, O., Liu, C.: Spherical parameter detection based on hierarchical Hough transform. Pattern Recognition Letters 27(9), 980–986 (2006)
Rabbani, T., Van Den Heuvel, F.: Efficient Hough transform for automatic detection of cylinders in point clouds. ISPRS WG III/3, III/4 3, 60–65 (2005)
Tarsha-Kurdi, F., Landes, T., Grussenmeyer, P.: Hough-transform and extended RANSAC algorithms for automatic detection of 3D building roof planes from lidar data. International Archives of Photogrammetry. Remote Sensing and Spatial Information Systems 36, 407–412 (2007)
Kotthäuser, T., Mertsching, B.: Triangulation-based plane extraction for 3D point clouds. In: Su, C.-Y., Rakheja, S., Liu, H. (eds.) ICIRA 2012, Part I. LNCS, vol. 7506, pp. 217–228. Springer, Heidelberg (2012)
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Abuzaina, A., Nixon, M.S., Carter, J.N. (2013). Sphere Detection in Kinect Point Clouds via the 3D Hough Transform. In: Wilson, R., Hancock, E., Bors, A., Smith, W. (eds) Computer Analysis of Images and Patterns. CAIP 2013. Lecture Notes in Computer Science, vol 8048. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40246-3_36
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DOI: https://doi.org/10.1007/978-3-642-40246-3_36
Publisher Name: Springer, Berlin, Heidelberg
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