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Handling Occlusions for Robust Augmented Reality Systems

机译:处理健壮的增强现实系统的遮挡

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In Augmented Reality applications, the human perception is enhanced with computer-generated graphics. These graphics must be exactly registered to real objects in the scene and this requires an effective Augmented Reality system to track the user's viewpoint. In this paper, a robust tracking algorithm based on coded fiducials is presented. Square targets are identified and pose parameters are computed using a hybrid approach based on a direct method combined with the Kalman filter. An important factor for providing a robust Augmented Reality system is the correct handling of targets occlusions by real scene elements. To overcome tracking failure due to occlusions, we extend our method using an optical flow approach to track visible points and maintain virtual graphics overlaying when targets are not identified. Our proposed real-time algorithm is tested with different camera viewpoints under various image conditions and shows to be accurate and robust.
机译:在增强现实应用程序中,计算机生成的图形增强了人类的感知能力。这些图形必须准确地注册到场景中的真实对象,这需要有效的增强现实系统来跟踪用户的视点。本文提出了一种基于编码基准的鲁棒跟踪算法。使用基于直接方法结合卡尔曼滤波器的混合方法,识别方形目标并计算姿势参数。提供强大的增强现实系统的重要因素是真实场景元素对目标遮挡的正确处理。为了克服由于遮挡而导致的跟踪失败,我们使用光流方法扩展了我们的方法,以跟踪可见点并在未识别目标时保持虚拟图形覆盖。我们提出的实时算法在各种图像条件下使用不同的摄像机视点进行了测试,结果证明该算法是准确且可靠的。

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