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Accuracy Analysis of Augmented Reality Markers for Visual Mapping and Localization

机译:用于视觉映射和定位增强现实标记的准确性分析

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An important problem that can be solved by Computer Vision algorithms is computing a 3D reconstruction of a scene captured by an ordinary camera. While some approaches seek solutions based on natural features (projections of the captured scene in the image), artificial markers can be used as an attractive alternative because they are easier to detect and less susceptible to error. Several artificial markers systems are available as computer libraries with different approaches of camera pose estimation, although their capabilities are still unexplored by Simultaneous Localization and Mapping (SLAM) solutions. This work presents a solution to the problem of SLAM using artificial markers. The automatically computed camera poses by the ARUCO library are assessed on data depicting commonly encountered scenarios in Robotics and Augmented/Virtual Reality applications, such as small to medium sized rooms and a research laboratory. The evaluation considers an established criteria that should clarify the accuracy of the use of artificial markers in visual mapping and localization.
机译:计算机视觉算法可以解决的重要问题是计算由普通摄像机捕获的场景的3D重建。虽然某些方法是基于自然特征的寻求解决方案(图像中捕获的场景的投影),但是人工标记可以用作有吸引力的替代方案,因为它们更容易检测和更易受错误的影响。几种人工标记系统可作为计算机库提供具有不同的相机姿势估计方法,尽管它们的功能仍然是通过同时本地化和映射(SLAM)解决方案而无法开发的。这项工作提出了使用人工标志物的解决问题的解决方案。 ARUCO库的自动计算的相机姿势被评估了描绘了机器人中的通常遇到的场景和增强/虚拟现实应用的数据,例如小于中型房间和研究实验室。评估考虑了建立的标准,该标准应该澄清在视觉映射和本地化中使用人工标志的准确性。

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