Fast volume calibration and occlusion free depth estimation using enhanced optical orthogonal codes

Lakshmi Sravya Koppula, I. Kiran, K. Venkatesh
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Abstract

Structured light techniques have received increased attention for depth estimation as they are robust and accurate. In this paper, we propose a method for camera-projector calibration which is required for structured light based depth estimation. We also propose enhancements to the existing hierarchical orthogonal coding (HOC) technique. The proposed space calibration technique is simple and fast compared to current camera-projector calibration techniques. The existing HOC, though being robust to ambient environmental lighting conditions, fails at occluded regions due to its pixel decoding strategy. With this in mind, we propose a self occlusion detection method to detect such ‘shadows’ in advance and to recommend to readjust the camera-projector positions to eliminate the shadows. Additionally an address transition rule is also proposed to correct any erroneously detected code. The proposed method is evaluated by computing the depth maps of objects of different known shapes.
使用增强的光学正交码快速体积校准和无遮挡深度估计
结构光技术因其鲁棒性和准确性而受到越来越多的关注。在本文中,我们提出了一种基于结构光的深度估计所需的相机-投影仪校准方法。我们还提出了对现有的分层正交编码(HOC)技术的改进。与目前的摄像机-投影仪标定技术相比,本文提出的空间标定技术简单、快速。现有的HOC虽然对环境光照条件具有鲁棒性,但由于其像素解码策略,在遮挡区域无法实现。考虑到这一点,我们提出了一种自我遮挡检测方法来提前检测这种“阴影”,并建议重新调整相机-投影仪的位置以消除阴影。此外,还提出了一个地址转换规则来纠正任何错误检测的代码。通过计算已知不同形状物体的深度图来评估所提出的方法。
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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