TOF相机实时高精度深度误差补偿方法

TOF(Time-Of-Flight)相机获取的深度值存在着边角畸变和精度偏移, 目前主要是通过误差查找表或曲线拟合等技术进行误差补偿, 计算量大且补偿速度慢。通过对TOF相机在不同距离的深度误差分布规律的分析, 提出了一种实时、高精度的误差补偿方法。该方法利用TOF深度图像的旋转对称性以及误差分布的特性, 简化了误差补偿模型、降低参数数量级, 有效提升了补偿的精度和速度。将算法应用于基于TOF原理的Kinect v2深度传感器进行深度补偿, 使得有效距离内平面度误差下降到0.63 mm内, 平均误差下降到0.704 0 mm内, 单帧数据补偿时间在90 ms内。由于该算法仅基于光径差进行补偿, 因此适用于所有TOF原理的相机。实验结果表明, 该算法能够快速有效减少TOF相机的深度误差, 适用于实时、高精度的大视场三维重建。

Abstract

When using Time-Of-Flight(TOF) camera to obtain depth values, corner distortion and precision offset often occur. At present, the main methods to compensate depth errors are based on the techniques like error look-up table or curve fitting, which has a large amount of calculation resulting in slow compensation speed. By analyzing the depth error distribution law of TOF camera at different distances, a real-time and high-precision error compensation method was proposed. The error compensation model was simplifed by using the rotational symmetry of TOF depth image and the characteristics of error distribution. The order of magnitude of the parameters was reduced, and the accuracy and speed of compensation process were effectively improved. The proposed algorithm was applied to Kinect v2 depth sensor for depth compensation, the flatness error within the effective distance dropped to 0.63 mm, the average error dropped to 0.704 0 mm, and the single frame data compensation time was less than 90 ms. Since the algorithm compensates only based on the optical path difference, it is suitable for all TOF principle cameras. The results of experiments show that the proposed algorithm can quickly and effectively reduce the depth error of TOF camera, and is suitable for real-time, high-precision three-dimensional reconstruction of large field of view.

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TOF相机实时高精度深度误差补偿方法

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