The design and analysis of spatial data structures
The design and analysis of spatial data structures
Three-dimensional medical imaging: algorithms and computer systems
ACM Computing Surveys (CSUR)
Making large-scale support vector machine learning practical
Advances in kernel methods
Computational Geometry: Theory and Applications
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Support vector machine learning for interdependent and structured output spaces
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Online Surface Reconstruction from Unorganized 3D-Points for the DLR Hand-Guided Scanner System
3DPVT '04 Proceedings of the 3D Data Processing, Visualization, and Transmission, 2nd International Symposium
Hierarchical Splatting of Scattered Data
Proceedings of the 14th IEEE Visualization 2003 (VIS'03)
Toward Reliable Off Road Autonomous Vehicles Operating in Challenging Environments
International Journal of Robotics Research
Point-based multiscale surface representation
ACM Transactions on Graphics (TOG)
Data Structures for Efficient Dynamic Processing in 3-D
International Journal of Robotics Research
A multi-resolution pyramid for outdoor robot terrain perception
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Efficient proximity search for 3-D cuboids
ICCSA'03 Proceedings of the 2003 international conference on Computational science and its applications: PartIII
Octree-based point-cloud compression
SPBG'06 Proceedings of the 3rd Eurographics / IEEE VGTC conference on Point-Based Graphics
Data Structures for Efficient Dynamic Processing in 3-D
International Journal of Robotics Research
Onboard contextual classification of 3-D point clouds with learned high-order Markov random fields
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
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This paper considers the problem of the dynamic processing of large amounts of sparse three-dimensional data. It is assumed that computations are performed in a neighborhood defined around each point in order to retrieve local properties. This general kind of processing can be applied to a wide variety of problems. A new, efficient data structure and corresponding algorithms are proposed that significantly improve the speed of the range search operation and that are suitable for on-line operation where data is accumulated dynamically. The method relies on taking advantage of overlapping neighborhoods and the reuse of previously computed data as the algorithm scans each data point. To demonstrate the dynamic capabilities of the data structure, data obtained from a laser radar mounted on a ground mobile robot operating in complex, outdoor environments is used. It is shown that this approach considerably improves the speed of an established 3-D perception processing algorithm.