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3D Keypoints Detection from a 3D Point Cloud for Real-Time Camera Tracking

3D Keypoints Detection from a 3D Point Cloud for Real-Time Camera Tracking

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カテゴリ: 論文誌(論文単位)

グループ名: 【C】電子・情報・システム部門

発行日: 2013/01/01

タイトル(英語): 3D Keypoints Detection from a 3D Point Cloud for Real-Time Camera Tracking

著者名: Baowei Lin (Department of Information Engineering, Graduate School of Engineering, Hiroshima University), Toru Tamaki (Department of Information Engineering, Graduate School of Engineering, Hiroshima University), Marcos Slomp (Department of Information En

著者名(英語): Baowei Lin (Department of Information Engineering, Graduate School of Engineering, Hiroshima University), Toru Tamaki (Department of Information Engineering, Graduate School of Engineering, Hiroshima University), Marcos Slomp (Department of Information Engineering, Graduate School of Engineering, Hiroshima University), Bisser Raytchev (Department of Information Engineering, Graduate School of Engineering, Hiroshima University), Kazufumi Kaneda (Department of Information Engineering, Graduate School of Engineering, Hiroshima University), Koji Ichii (Department of Information Engineering, Graduate School of Engineering, Hiroshima University)

キーワード: 3D keypoints,3D-2D matching,point cloud,feature descriptor,real-time,camera tracking

要約(英語): In this paper we propose a method for detecting 3D keypoints in a 3D point cloud for robust real-time camera tracking. Assuming that there are a number of images corresponding to the 3D point cloud, we define a 3D keypoint as a point that has corresponding 2D keypoints in many images. These 3D keypoints are expected to appear with high probability as 2D keypoints in newly taken query images. For 3D-2D matching, we embed 2D feature descriptors into the 3D keypoints. Experimental results with 3D point clouds of indoor and outdoor scenes show that the extracted 3D keypoints can be used for matching with 2D keypoints in query images.

本誌: 電気学会論文誌C(電子・情報・システム部門誌) Vol.133 No.1 (2013) 特集:2012 Korea-Japan Joint Workshop on Frontiers of Computer Vision (FCV2012)

本誌掲載ページ: 84-90 p

原稿種別: 論文/英語

電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejeiss/133/1/133_84/_article/-char/ja/

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