一种基于目标检测和PnP的移动终端室内定位方法

针对传统的视觉定位易受噪声干扰、目标检测准确率低且无法获取终端准确位姿信息的问题，提出了一种基于卷积神经网络的目标检测和PnP相结合的移动终端室内定位方法，通过Mask-RCNN进行目标检测，然后采用EPnP算法求解相机准确的位姿信息，并对该方法进行系统实现及真实场景试验。试验结果表明，该方法目标检测准确率在98%以上，单轴定位误差在0.35 m以内，满足移动终端室内定位的精度，具有精度高、稳定性好的优点，为基于视觉的移动终端室内定位提供了新的思路。

A method for indoor location of mobile terminal based on target detection and PnP

Aiming at the problem that traditional visual positioning is susceptible to noise interference, the accuracy of target detection is low and the accurate pose information cannot be obtained, this paper proposes an indoor positioning method of mobile terminal based on convolution neural network for target detection and PnP. The target detection is carried out by Mask-RCNN, and the accurate pose information of camera is obtained by EPnP algorithm. The method is implemented systematically and experimented in real scenes. The experimental results show that the target detection accuracy is more than 98%, the single-axis positioning error is less than 0.35 m, which meets the accuracy of indoor positioning of mobile terminals, and has the advantages of high precision and good stability. It provides a new idea for indoor positioning of mobile terminal based on vision.