A common goal of outdoor augmented reality (AR) is the presentation of annotations that are registered to anchor points in the real world. We present an enhanced approach for registering and tracking such anchor points, which is suitable for current generation mobile phones and can also successfully deal with the wide variety of viewing conditions encountered in real life outdoor use. The approach is based on on-the-fly generation of panoramic images by sweeping the camera over the scene. The panoramas are then used for stable orientation tracking, while the user is performing only rotational movements. This basic approach is improved by several new techniques for the re-detection and tracking of anchor points. For the re-detection, specifically after temporal variations, we first compute a panoramic image with extended dynamic range, which can better represent varying illumination conditions. The panorama is then searched for known anchor points, while orientation tracking continues uninterrupted. We then use information from an internal orientation sensor to prime an active search scheme for the anchor points, which improves matching results. Finally, global consistency is enhanced by statistical estimation of a global rotation that minimizes the overall position error of anchor points when transforming them from the source panorama in which they were created, to the current view represented by a new panorama. Once the anchor points are redetected, we track the user's movement using a novel 3-degree-of-freedom orientation tracking approach that combines vision tracking with the absolute orientation from inertial and magnetic sensors. We tested our system using an AR campus guide as an example application and provide detailed results for our approach using an off-the-shelf smartphone. Results show that the re-detection rate is improved by a factor of 2 compared to previous work and reaches almost 90% for a wide variety of test cases while still keeping the ability to run at interactive frame rates.

中文翻译：

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户外增强现实浏览注释的鲁棒检测和跟踪

户外增强现实 (AR) 的一个共同目标是呈现注册到现实世界中的锚点的注释。我们提出了一种用于注册和跟踪此类锚点的增强方法，它适用于当前一代手机，也可以成功处理现实生活中户外使用中遇到的各种观看条件。该方法基于通过将相机扫过场景来即时生成全景图像。然后将全景图用于稳定的方向跟踪，而用户仅执行旋转运动。这种基本方法通过几种用于重新检测和跟踪锚点的新技术得到了改进。对于重新检测，特别是在时间变化之后，我们首先计算具有扩展动态范围的全景图像，可以更好地代表不同的光照条件。然后在全景图中搜索已知的锚点，同时方向跟踪继续不间断。然后，我们使用来自内部方向传感器的信息为锚点启动主动搜索方案，从而改善匹配结果。最后，通过全局旋转的统计估计增强了全局一致性，当将锚点从创建它们的源全景图转换到由新全景图表示的当前视图时，该旋转最小化了锚点的整体位置误差。一旦重新检测到锚点，我们就会使用一种新颖的 3 自由度方向跟踪方法来跟踪用户的运动，该方法将视觉跟踪与来自惯性和磁传感器的绝对方向相结合。我们使用 AR 校园指南作为示例应用程序测试了我们的系统，并使用现成的智能手机为我们的方法提供了详细的结果。结果表明，与之前的工作相比，重新检测率提高了 2 倍，并且在各种测试用例中达到近 90%，同时仍保持以交互帧速率运行的能力。