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The RGB-D SLAM augmented reality log measurement system was constructed, which used a smart phone embedded with a ToF camera, RGB camera and IMU as the hardware system, and used the depth map and pose acquired by RGB-D SLAM technology as the data source. Specifically, the method for online estimating the pixel depth of RGB images was designed based on ToF images in order to preliminarily estimate the position of log end faces; secondly, a denoising algorithm based on discrete partitioning and a log end face curvature estimation algorithm were designed for precisely filtering the log end point cloud and evaluating the reliability of the filtering results; then, the PCA algorithm was used to estimate the length and diameter direction vector of the log, which was used to estimate the value of the length and diameter of the log; and finally, the algorithm was used to build a log measurement system on the mobile phone platform, so as to realize the online measurement of the log diameter by using the smart phone, and the online supervision of the measurement results by using the augmented reality scene. The system was tested by measuring 334 logs in six regions to evaluate the measurement accuracy. The results showed that the bias and root mean square error (RMSE) of the log diameter estimates were -0.13cm (-0.35%) and 1.05cm (3.34%) respectively; the bias and RMSE of the log stepping diameter estimates were -0.10cm (-0.22%) and 1.33cm (4.43%) respectively; the bias and RMSE of the log volume estimates were -0.007m3(-0.27%) and 0.0939m3(7.23%) respectively; the absolute value of the relative error of the volume of log pile was no more than 2.23%; and the error of the total volume of all log piles was -0.68%. Obviously, no matter from the point of view of a single log or a pile, the measurement results were unbiased and high-precision, which meant that the new log measuring system was a potential highprecision, high-robust real-time log measuring potential solutions.