Agile Depth Sensing Using Triangulation Light Curtains

Joseph R. Bartels, Jian Wang, W. Whittaker, S. Narasimhan
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引用次数: 20

Abstract

Depth sensors like LIDARs and Kinect use a fixed depth acquisition strategy that is independent of the scene of interest. Due to the low spatial and temporal resolution of these sensors, this strategy can undersample parts of the scene that are important (small or fast moving objects), or oversample areas that are not informative for the task at hand (a fixed planar wall). In this paper, we present an approach and system to dynamically and adaptively sample the depths of a scene using the principle of triangulation light curtains. The approach directly detects the presence or absence of objects at specified 3D lines. These 3D lines can be sampled sparsely, non-uniformly, or densely only at specified regions. The depth sampling can be varied in real-time, enabling quick object discovery or detailed exploration of areas of interest. These results are achieved using a novel prototype light curtain system that is based on a 2D rolling shutter camera with higher light efficiency, working range, and faster adaptation than previous work, making it useful broadly for autonomous navigation and exploration.
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使用三角光幕的敏捷深度传感
像lidar和Kinect这样的深度传感器使用独立于感兴趣的场景的固定深度获取策略。由于这些传感器的空间和时间分辨率较低,这种策略可能会对场景中重要的部分(小或快速移动的物体)进行欠采样,或者对手头任务(固定的平面墙)没有信息的区域进行过采样。本文提出了一种利用三角光幕原理对场景深度进行动态自适应采样的方法和系统。该方法直接检测指定3D线上物体的存在或不存在。这些3D线可以稀疏采样,不均匀采样,或者只在指定区域密集采样。深度采样可以实时变化,可以快速发现目标或对感兴趣的区域进行详细探索。这些结果是通过一种基于2D卷帘式相机的新型原型光幕系统实现的,该系统具有更高的光效、工作范围和比以前工作更快的适应性,使其在自主导航和探索中广泛应用。
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