Non-pre-process calibration of depth image based on fuzzy c-mean

C. Liang, S. Su, Ming-Chang Chen
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引用次数: 1

Abstract

In this paper, a non-preprocess calibration of depth image is proposed Take advantage of FCM to acquire the depth value distribution in the depth image. After that, according to relation among all the centroids of cluster, the real distance is estimated. Then, the error of the depth value is able to be compensated. When utilize the proposed method, plenty of pre-process for calibration can be avoided, such as using chessboard to capture the camera parameters, or recording measurement error in advance. Therefore, time cost, inconvenient, and human error for calibration can be reduced significantly. Utilize the proposed method can offer the users a reliable depth camera without traditional calibration procedure. At last, the proposed method is verified by comparing the consequents with traditional depth calibration and laser rangefinder. The results show it has an outstanding performance.
基于模糊c均值的深度图像非预处理定标
本文提出了一种深度图像的非预处理定标方法,利用FCM获取深度图像中的深度值分布。然后,根据聚类所有质心之间的关系,估计出实际距离。然后,可以补偿深度值的误差。利用该方法可以避免大量的校准前处理,如使用棋盘捕捉相机参数,或提前记录测量误差。因此,可以大大减少校准的时间成本、不方便和人为误差。利用该方法可以为用户提供可靠的深度相机,而无需传统的校准程序。最后,通过与传统深度标定和激光测距仪标定结果的比较,验证了所提方法的有效性。结果表明,该方法具有优异的性能。
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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