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BIM-Tracker: A model-based visual tracking approach for indoor localisation using a 3D building model

机译:BIM-Tracker:使用3D建筑模型的室内本地化基于模型的视觉跟踪方法

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This article presents an accurate and robust visual indoor localisation approach that not only is infrastructure free, but also avoids accumulation error by taking advantage of (1) the widespread ubiquity of mobile devices with cameras and (2) the availability of 3D building models for most modern buildings. Localisation is performed by matching image sequences captured by a camera, with a 3D model of the building in a model-based visual tracking framework. Comprehensive evaluation of the approach with a photo-realistic synthetic dataset shows the robustness of the localisation approach under challenging conditions. Additionally, the approach is tested and evaluated on real data captured by a smartphone. The results of the experiments indicate that a localisation accuracy better than 10 cm can be achieved by using this approach. Since localisation errors do not accumulate the proposed approach is suitable for indoor localisation tasks for long periods of time and augmented reality applications, without requiring any local infrastructure. A MATLAB implementation can be found on https://github.com/debaditya-unimelb/BIM-Tracker.
机译:本文介绍了一个准确且强大的视觉室内本地化方法,不仅可以免费实现基础设施,而且还通过利用(1)使用摄像机的移动设备的广泛浮动设备和(2)大多数3D建筑模型的可用性来避免累积误差现代建筑。通过在基于模型的视觉跟踪框架中匹配相机捕获的图像序列来执行本地化,以模型的视觉跟踪框架中的建筑物的3D模型来执行。使用照片逼真的合成数据集的方法综合评价显示了本地化方法在挑战条件下的稳健性。此外,该方法是在由智能手机捕获的真实数据上进行测试和评估。实验结果表明,通过使用这种方法可以实现优于10cm的定位精度。由于本地化错误不会累积,所提出的方法适用于长时间的室内定位任务和增强现实应用,而无需任何本地基础架构。可以在https://github.com/debaditya-unimelb/bim-tracker上找到matlab实现。

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