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

Daniel de Andrade Lemeszenski, L. R. Nakamura
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引用次数: 2

Abstract

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.
基于结构光传感器的多深度图无标记标定配准方法及其在视频Avatar系统中的应用
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的化身进行建模。为了创建更完整的用户3D几何表示,通常需要一个复杂的校准过程,使用标记来注册来自多个3D相机的流。本文提出了一种无标记配准过程,用于使用多个结构光传感器创建代表人体表面的全局模型。除此之外,这种方法通过向设置中添加新设备来实现更大的可伸缩性。本文还介绍了两个实验来验证该设置的可行性,第一个实验涉及同时使用两个感染的噪声测量,第二个实验涉及对多个深度图配准的ICP算法行为的评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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