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Augmenting Microsofts HoloLens with vuforia tracking for neuronavigation

机译:通过vuforia跟踪神经导航增强Microsoft的HoloLens

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摘要

Major hurdles for Microsoft's HoloLens as a tool in medicine have been accessing tracking data, as well as a relatively high-localisation error of the displayed information; cumulatively resulting in its limited use and minimal quantification. The following work investigates the augmentation of HoloLens with the proprietary image processing SDK Vuforia, allowing integration of data from its front-facing RGB camera to provide more spatially stable holograms for neuronavigational use. Continuous camera tracking was able to maintain hologram registration with a mean perceived drift of 1.41 mm, as well as a mean sub 2-mm surface point localisation accuracy of 53%, all while allowing the researcher to walk about a test area. This represents a 68% improvement for the later and a 34% improvement for the former compared with a typical HoloLens deployment used as a control. Both represent a significant improvement on hologram stability given the current state-of-the-art, and to the best of the authors knowledge are the first example of quantified measurements when augmenting hologram stability using data from the RGB sensor.
机译:微软的HoloLens作为医学工具的主要障碍一直在访问跟踪数据以及所显示信息的相对较高的本地化错误。累积导致其使用受限和数量最少。以下工作研究了专有图像处理SDK Vuforia对HoloLens的增强作用,从而允许其前端RGB相机的数据集成在一起,从而为神经导航提供更稳定的全息图。连续的摄像头跟踪能够保持全息图配准,其平均感知漂移为1.41 mm,平均2毫米以下亚表面点定位精度为53%,同时使研究人员能够在测试区域中行走。与用作控件的典型HoloLens部署相比,后者的性能提高了68%,前者的性能提高了34%。鉴于当前的最新技术,两者都代表了全息图稳定性的重大改进,并且据作者所知,这是使用来自RGB传感器的数据增强全息图稳定性时量化测量的第一个示例。

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