张帆, 孙晓辉, 崔东林. 基于ORB特征的矿井移动目标双目视觉跟踪与定位[J]. 煤炭学报, 2018, 43(S2): 654-662. DOI: 10.13225/j.cnki.jccs.2017.1650
引用本文: 张帆, 孙晓辉, 崔东林. 基于ORB特征的矿井移动目标双目视觉跟踪与定位[J]. 煤炭学报, 2018, 43(S2): 654-662. DOI: 10.13225/j.cnki.jccs.2017.1650
ZHANG Fan, SUN Xiao-hui, CUI Dong-lin. Method of tracking and positioning for mobile target based on ORB features and binocular vision in mine[J]. Journal of China Coal Society, 2018, 43(S2): 654-662. DOI: 10.13225/j.cnki.jccs.2017.1650
Citation: ZHANG Fan, SUN Xiao-hui, CUI Dong-lin. Method of tracking and positioning for mobile target based on ORB features and binocular vision in mine[J]. Journal of China Coal Society, 2018, 43(S2): 654-662. DOI: 10.13225/j.cnki.jccs.2017.1650

基于ORB特征的矿井移动目标双目视觉跟踪与定位

Method of tracking and positioning for mobile target based on ORB features and binocular vision in mine

  • 摘要: 针对井下NLOS环境信号接收强度 (RSSI) 和飞行时间 (ToF) 定位方法存在多径干扰和定位时延, 导致定位误差较大问题, 提出了基于ORB特征的矿井移动目标双目视觉跟踪与定位方法。首先根据矿井移动目标双目视觉跟踪与定位原理, 利用RSSI阈值监测井下移动目标的位置范围, 据此触发双目视觉传感器对移动目标图像信息采样和特征提取;然后对采集的目标图像与训练图像进行ORB算法特征匹配;最后根据双目视觉传感器的视差均值和图像像素坐标公式, 求解相机内外参矩阵和标定移动目标的世界坐标, 从而获取井下移动目标的准确位置信息, 实现实时跟踪与精确定位。结果表明, 与其他算法相比, 本文方法能够有效提高定位精度和实时性, 对井下目标遮挡、低照度和噪声环境具有较强的鲁棒性。

     

    Abstract: In order to solve the problem of location error, which caused by multipath interference and time delay in NLOS environment of mine based on location method of signal receiving intensity (RSSI) and time of flight (ToF), a binocular vision tracking and positioning method for mine moving target based on ORB feature is proposed.Firstly, through establishing the binocular vision tracking and positioning model of mine moving target, using the RSSI threshold to monitor the position range of underground moving target, the binocular vision sensor is triggered to do the image information sampling and feature extraction of moving target.After that, the target image and the training image are matched by the ORB algorithm.Finally, according to the parallax mean and the pixel coordinate formula of binocular vision sensor, the coordinates of the camera's internal and external parameters and the coordinates of the moving target are calculated.Therefore, the accurate location information of the mine moving target is obtained to realize a real-time tracking and accurate positioning.The results show that, compared with other algorithms, the proposed method can effectively improve the positioning accuracy and real-time performance, and has strong robustness to the tracking and positioning of moving objects under the target occlusion, low illumination and noise environment.

     

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