Capturing 2 1/2 D depth and texture of time-varying scenes using structured infrared light

Capturing 2 1/2 D depth and texture of time-varying scenes using structured infrared light
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使用结构红外光捕捉时变场景的 2 1/2 D 深度和纹理

DOI:
10.1109/3dim.2005.26
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发表时间:
2005
期刊:
Fifth International Conference on 3-D Digital Imaging and Modeling (3DIM'05)
影响因子:
--
通讯作者:
A. Zakhor
A. Zakhor
中科院分区:
--
文献类型:
--
作者:
Christian Früh;A. Zakhor

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在本文中,我们描述了一种方法,同时捕捉视觉外观和深度的时变场景。我们的方法是基于投影结构化红外(IR)光。具体地说,我们项目的组合(a)一个静态的垂直红外条纹图案,和(B)一个水平的红外激光线扫描的场景,在同一时间,该场景被捕获的红外敏感相机。由于红外光对人眼是不可见的,因此它不会干扰人类主体或干扰场景中的人类活动;此外,它不会影响彩色摄像机记录的场景的视觉外观。使用水平线、帧内跟踪和帧间跟踪来识别IR帧中的垂直线;经由三角测量来重构沿着这些线的深度沿着。将这些稀疏的深度线内插到所记录的视频序列的前景轮廓内,我们获得视频序列中的每一帧的密集深度图。实验结果表明,我们所提出的方法的有效性,相应的动态场景与运动中的人类主体。
In this paper, we describe an approach to simultaneously capture visual appearance and depth of a time-varying scene. Our approach is based on projecting structured infrared (IR) light. Specifically, we project a combination of (a) a static vertical IR stripe pattern, and (b) a horizontal IR laser line sweeping up and down the scene; at the same time, the scene is captured with an IR-sensitive camera. Since IR light is invisible to the human eye, it does not disturb human subjects or interfere with human activities in the scene; in addition, it does not affect the scene's visual appearance as recorded by a color video camera. Vertical lines in the IR frames are identified using the horizontal line, intra-frame tracking, and inter-frame tracking; depth along these lines is reconstructed via triangulation. Interpolating these sparse depth lines within the foreground silhouette of the recorded video sequence, we obtain a dense depth map for every frame in the video sequence. Experimental results corresponding to a dynamic scene with a human subject in motion are presented to demonstrate the effectiveness of our proposed approach.
大尺度空间中 3D 视频的可缩放 3D 表示
DOI: --
发表时间: 2004
期刊: Presence 13・2
影响因子: --
作者:
Itaru Kitahara;Yuichi Ohta
通讯作者: Yuichi Ohta
录制多个视频并在大范围空间内进行3D视频显示
DOI: --
发表时间: 2003
期刊: Proceedings of IEEE Conference on Multisensor Fusion and Integration for Intelligent Systems
影响因子: --
作者:
Itaru Kitahara;Yuichi Ohta
通讯作者: Yuichi Ohta