Continuous and automatic registration of live RGBD video streams with partial overlapping views

Afsaneh Rafighi, S. Seifi, Oscar E. Meruvia Pastor
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Abstract

This paper presents a novel method for automatic registration of video streams originated from two depth-sensing cameras. The system consists of a sender and receiver, in which the sender obtains the streams from two RGBD sensors placed arbitrarily around a room and produces a unified scene as a registered point cloud. A conventional method to support a multi-depth sensor system is through calibration. However, calibration methods are time consuming and require the use of external markers prior to streaming. If the cameras are moved, calibration has to be repeated. The motivation of this work is to facilitate the use of RGBD sensors for non-expert users, so that cameras need not to be calibrated, and if cameras are moved, the system will automatically recover the alignment of the video streams. DeReEs [Seifi et al. 2014], a new registration algorithm, is used, since it is fast and successful in registering scenes with small overlapping sections.
连续和自动注册实时RGBD视频流与部分重叠视图
本文提出了一种基于深度感测器的视频流自动配准方法。该系统由发送方和接收方组成,其中发送方从任意放置在房间周围的两个RGBD传感器获取流,并产生统一的场景作为配准点云。支持多深度传感器系统的传统方法是通过校准。然而,校准方法是耗时的,并且需要在流式传输之前使用外部标记。如果摄像机移动,则必须重复校准。这项工作的动机是为了方便非专业用户使用RGBD传感器,这样摄像机就不需要校准,如果摄像机被移动,系统将自动恢复视频流的对齐。使用了一种新的配准算法deees [Seifi et al. 2014],因为它可以快速成功地配准具有小重叠部分的场景。
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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