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Railway Object Recognition Using Mobile Laser Scanning Data
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모바일 레이저 스캐닝 데이터로부터 철도 시설물 인식에 관한 연구

논문 기본 정보

Type
Academic journal
Author
LUO CHAO (요크대학교) Yoon Seok Jwa (요크대학교) Gun Ho Sohn (요크대학교) Jong Un Won (한국철도기술연구원) Suk Lee (한국철도기술연구원)
Journal
Korea Society of Industrial Informantion Systems Journal of the Korea Industrial Information Systems Research Vol.19 No.2 KCI Accredited Journals
Published
2014.4
Pages
85 - 91 (7page)

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Method
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Result
Railway Object Recognition Using Mobile Laser Scanning Data
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Abstract· Keywords

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The objective of the research is to automatically recognize railway objects from MLS data in which 9 key objects including terrain, track, bed, vegetation, platform, barrier, posts, attachments, powerlines are targeted. The proposed method can be divided into two main sub-steps. First, multi-scale contextual features are extracted to take the advantage of characterizing objects of interest from different geometric levels such as point, line, volumetric and vertical profile. Second, by considering contextual interactions amongst object labels, a contextual classifier is utilized to make a prediction with local coherence. In here, the Conditional Random Field (CRF) is used to incorporate the object context. By maximizing the object label agreement in the local neighborhood, CRF model could compensate the local inconsistency prediction resulting from other local classifiers. The performance of proposed method was evaluated based on the analysis of commission and omission error and shows promising results for the practical use.
#철도시설물 인식 #Conditional Random Field #맥락 분류 #모바일 레이저 스캐닝 #Railway Object Recognition #Conditional Random Field #Contextual Classifier #Mobile Laser Scanning

Contents

요약
Abstract
1. 서론
2. 연구의 범위 및 연구동향
3. 철도 시설물 분류 알고리즘
4. 실험 및 결과
5. 결론 및 향후연구
References

References (15)

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1. [학술지(정기간행물)] - M. Neubert. / 2008 / Extraction of Railroad Objects from Very High Resolution Helicopter-borne LiDAR and Ortho-image Data / International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences 38 (4) : 25 ~ 30 google schola 2. [학술지(정기간행물)] - B. Beger. / 2011 / Data Fusion of Extremely High Resolution Aerial Imagery and LiDAR Data for Automated Railroad Centre Line Recontruction / ISPRS Journal of Photogrammetry and Remote Sensing 66 (6) : 40 ~ 51 google schola 3. [학술지(정기간행물)] - J. Yoon. / 2009 / Feature extraction of a concrete tunnel liner from 3D laser scanning data / NDT & E INTERNATIONAL 42 (2) : 97 ~ 105 google schola 4. [학술지(정기간행물)] - S. Pu. / 2011 / Recognizing Basic Structures from Mobile Laser Scanning Data for Road Inventory Studies / ISPRS Journal of Photogrammetry and Remote Sensing 66 (6) : 28 ~ 39 google schola 5. [학술대회논문] - A. Golovinskiy. / 2009 / Shape-based Recognition of 3D Point Clouds in Urban Environments / Computer Vision : 1 ~ 8 google schola

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