Abstract: | |
With an increasing interest in indoor location based services, vision-based indoor localization techniques have attracted many attentions from both academia and industry. Inspired by the development of simultaneous localization and mapping technique (SLAM), we present a visual SLAM-based approach to achieve a 6 degrees of freedom (DoF) pose in indoor environment. Firstly, the indoor scene is explored by a keyframe-based global mapping technique, which generates a database from a sequence of images covering the entire scene. After the exploration, a feature vocabulary tree is trained for accelerating feature matching in the image retrieval phase, and the spatial structures obtained from the keyframes are stored. Instead of querying by a single image, a short sequence of images in the query site are used to extract both features and their relative poses, which is a local visual SLAM procedure. The relative poses of query images provide a pose graph-based geometric constraint which is used to assess the validity of image retrieval results. The final positioning result is obtained by selecting the pose of the first correct corresponding image. © Authors 2019.
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License of this version: | CC BY 4.0 Unported - https://creativecommons.org/licenses/by/4.0/ |
Publication type: | BookPart |
Publishing status: | publishedVersion |
Publication date: | 2019 |
Keywords english: | Bag-of-visual-word, Geometric constraint, Image retrieval, Indoor localization, SLAM, Degrees of freedom (mechanics), Image retrieval, Location based services, Mapping, Query processing, Robotics, Telecommunication services, Bag-of-visual-words, Geometric constraint, Indoor environment, Indoor localization, Indoor localization techniques, Sequence of images, Simultaneous localization and mapping, SLAM, Indoor positioning systems |
DDC: | 550 | Geowissenschaften |
Controlled keywords(GND): | Konferenzschrift |
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