• Title/Summary/Keyword: 페어세트

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Multi Point Cloud Integration based on Observation Vectors between Stereo Images (스테레오 영상 간 관측 벡터에 기반한 다중 포인트 클라우드 통합)

  • Yoon, Wansang;Kim, Han-gyeol;Rhee, Sooahm
    • Korean Journal of Remote Sensing
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    • v.35 no.5_1
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    • pp.727-736
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    • 2019
  • In this paper, we present how to create a point cloud for a target area using multiple unmanned aerial vehicle images and to remove the gaps and overlapping points between datasets. For this purpose, first, IBA (Incremental Bundle Adjustment) technique was applied to correct the position and attitude of UAV platform. We generate a point cloud by using MDR (Multi-Dimensional Relaxation) matching technique. Next, we register point clouds based on observation vectors between stereo images by doing this we remove gaps between point clouds which are generated from different stereo pairs. Finally, we applied an occupancy grids based integration algorithm to remove duplicated points to create an integrated point cloud. The experiments were performed using UAV images, and our experiments show that it is possible to remove gaps and duplicate points between point clouds generated from different stereo pairs.

Research of Semantic Considered Tree Mining Method for an Intelligent Knowledge-Services Platform

  • Paik, Juryon
    • Journal of the Korea Society of Computer and Information
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    • v.25 no.5
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    • pp.27-36
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    • 2020
  • In this paper, we propose a method to derive valuable but hidden infromation from the data which is the core foundation in the 4th Industrial Revolution to pursue knowledge-based service fusion. The hyper-connected societies characterized by IoT inevitably produce big data, and with the data in order to derive optimal services for trouble situations it is first processed by discovering valuable information. A data-centric IoT platform is a platform to collect, store, manage, and integrate the data from variable devices, which is actually a type of middleware platforms. Its purpose is to provide suitable solutions for challenged problems after processing and analyzing the data, that depends on efficient and accurate algorithms performing the work of data analysis. To this end, we propose specially designed structures to store IoT data without losing the semantics and provide algorithms to discover the useful information with several definitions and proofs to show the soundness.