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학술지 Fast and Accurate Visual Place Recognition Using Street-View Images
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저자
이근동, 이승재, 정원조, 김기태
발행일
201702
출처
ETRI Journal, v.39 no.1, pp.97-107
ISSN
1225-6463
출판사
한국전자통신연구원 (ETRI)
DOI
https://dx.doi.org/10.4218/etrij.17.0116.0034
협약과제
16MS3400, 온-오프라인에서의 콘텐츠 비주얼 브라우징 기술 개발, 이승재
초록
A fast and accurate building-level visual place recognition method built on an image-retrieval scheme using street-view images is proposed. Reference images generated from street-view images usually depict multiple buildings and confusing regions, such as roads, sky, and vehicles, which degrades retrieval accuracy and causes matching ambiguity. The proposed practical database refinement method uses informative reference image and keypoint selection. For database refinement, the method uses a spatial layout of the buildings in the reference image, specifically a building-identification mask image, which is obtained from a prebuilt three-dimensional model of the site. A global-positioning-system-aware retrieval structure is incorporated in it. To evaluate the method, we constructed a dataset over an area of 0.26 km2. It was comprised of 38,700 reference images and corresponding building-identification mask images. The proposed method removed 25% of the database images using informative reference image selection. It achieved 85.6% recall of the top five candidates in 1.25 s of full processing. The method thus achieved high accuracy at a low computational complexity.
키워드
Database refinement, Image retrieval, Keypoint selection, Visual location search, Visual place recognition
KSP 제안 키워드
Fast and accurate, High accuracy, Image retrieval, Image selection, Low Computational Complexity, Mask image, Recognition method, Reference Image, Three dimensional(3D), Visual location, Visual place recognition