Abstract
Conventional Approaches to line segment matching have shown their performances less satisfactory mainly since some of the features used for matching, such as the center and the starting/ending points of line segments, are not invariant. Furthermore, a pair of line segment sets to be matched may not have one to one correspondence, but each can be a subset of the other. This led to multiple solutions or interpretations in matching, where finding out all the possible solutions or interpretations out of an arbitrarily overlapping pair of line segment is of an issue. This paper presents a general method of identifying all the possible solutions or interpretations for an arbitrary pair of line segment sets by using invariant features associated with line segments. The invariant property of line segments comes from the orientation and location contexts of line segments that are defined based on infinite line representation of individual line segments. Simulation and experiment shown the effectiveness of the proposed method compared to conventional methods.
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Acknowledgements
Sukhan Lee proposed and guided the algorithm for contexts matching, whereas implementation and experimentation are carried out by Kyungsang Cho and Jaewoong Kim. This research was supported, in part, by the “Technology Innovation Program (or Industrial Strategic Technology Development Program, Report Number: 10048320)”, sponsored by the Ministry of Trade, Industry & Energy (MOTIE), in part by the MSIP under the space technology development program (NRF-2016M1A3A9005563) supervised by the NRF and Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2017R1A6A3A11036554). This project is also supported by the “Project of e-Drive Train Platform Development for small and medium Commercial Electric Vehicles based on IoT Technology” of Korea Institute of Energy Technology Evaluation & Planning (KETEP) (20172010000420), sponsored by the Korea Ministry of Trade, Industry & Energy (MOTIE).
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Cho, K., Kim, J., Lee, S. (2019). Invariant 3D Line Context Feature for Instance Matching. In: Lee, S., Ismail, R., Choo, H. (eds) Proceedings of the 13th International Conference on Ubiquitous Information Management and Communication (IMCOM) 2019. IMCOM 2019. Advances in Intelligent Systems and Computing, vol 935. Springer, Cham. https://doi.org/10.1007/978-3-030-19063-7_37
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DOI: https://doi.org/10.1007/978-3-030-19063-7_37
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