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A Marker-Free Calibration and Registration Process for Multiple Depth Maps from Structured Light Sensors and its Application in Video Avatar Systems

机译:结构化光传感器的多个深度图的无标记校准和配准过程及其在视频头像系统中的应用

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Virtual and augmented reality systems for education, health and entertainment purposes may require the modeling of realistic avatars. In order to create a more complete 3D geometric representation of the user, it is often necessary a complex calibration process using markers for registering streams from multiple 3D cameras. This paper presents a proposal of a marker-free registration process for a global model creation that represents the human body surface using multiple structured light sensors. Besides that, this method allows greater scalability by the addition of new devices to the setup. The paper also covers two experiments to check the feasibility of this setup, the first one related to noise measurement using two infects simultaneously and the second one, an evaluation of ICP algorithm behavior for multiple depth maps registration.
机译:用于教育,健康和娱乐目的的虚拟和增强现实系统可能需要对现实化身进行建模。为了创建用户的更完整的3D几何表示,通常需要使用标记来注册来自多个3D摄像机的流的复杂校准过程。本文提出了一种用于全球模型创建的无标记注册过程的提议,该模型使用多个结构化的光传感器来代表人体表面。除此之外,该方法还可以通过在设置中添加新设备来实现更大的可扩展性。本文还涵盖了两个实验来检查这种设置的可行性,第一个实验与同时使用两个感染的噪声测量有关,第二个实验是针对多个深度图配准的ICP算法行为评估。

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