Recognition of Planar Segments in Point Cloud Based on Wavelet Transform
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© 2005-2012 IEEE.Within industrial automation systems, three-dimensional (3-D) vision provides very useful feedback information in autonomous operation of various manufacturing equipment (e.g., industrial robots, material handling devices, assembly systems, and machine tools). The hardware performance in contemporary 3-D scanning devices is suitable for online utilization. However, the bottleneck is the lack of real-time algorithms for recognition of geometric primitives (e.g., planes and natural quadrics) from a scanned point cloud. One of the most important and the most frequent geometric primitive in various engineering tasks is plane. In this paper, we propose a new fast one-pass algorithm for recognition (segmentation and fitting) of planar segments from a point cloud. To effectively segment planar regions, we exploit the orthonormality of certain wavelets to polynomial function, as well as their sensitivity to abrupt changes. After segmentation of planar regions, we estimate the parameters of corresponding planes using standard fitting procedures. For point cloud structuring, a z-buffer algorithm with mesh triangles representation in barycentric coordinates is employed. The proposed recognition method is tested and experimentally validated in several real-world case studies.
Published Version (Please cite this version)10.1109/TII.2015.2389195
Publication InfoJakovljevic, Z; Puzovic, R; & Pajic, M (2015). Recognition of Planar Segments in Point Cloud Based on Wavelet Transform. IEEE Transactions on Industrial Informatics, 11(2). pp. 342-352. 10.1109/TII.2015.2389195. Retrieved from https://hdl.handle.net/10161/10334.
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Dickinson Family Associate Professor
Miroslav Pajic's research focuses on design and analysis of cyber-physical systems with varying levels of autonomy and human interaction, at the intersection of (more traditional) areas of embedded systems, AI, learning and controls, formal methods and robotics.