智能手机移动测量方法的设计与实现
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摘要
近年来,智能手机在快速的发展过程中逐渐集成了多种传感器,包括位置传感器、磁力计和加速度计等姿态传感器和数码相机等;同时,由于它所具备的体积小、成本低的优点,为实现手机影像移动量测提供了可能。本文通过Android系统平台及智能手机集成的多传感器,提出了一种新型的智能手机影像量测方法。该方法首先对手机相机进行标定获取内方位元素,并进行Android应用程序的开发,在获取影像数据的同时获得手机的位置姿态数据;然后对影像数据进行特征点提取、匹配及错误点删除,并根据位置姿态数据和同名点图像坐标,利用空间前方交会计算目标点的三维坐标;最后通过光束法平差进行整体优化。试验结果表明该方法获取的位置信息可达到较高的精度。
In recent years,smartphones have gradually integrated a variety of sensors in the rapid development process,including position sensors,attitude sensors such as magnetometers,accelerometers and digital cameras. At the same time,the advantages of small size and low cost provide the possibility to realize mobile image measurement. A new type of smartphone image measurement method is proposed through the platform of Android system and multi-sensor integrated by smartphones. The method firstly calibrates the smartphone camera to obtain the inner orientation elements,and develops the Android application program which can obtain the position and posture data of the mobile phone while acquiring the image data. Secondly,extraction,matching of feature points and error point deletion are performed on the image data. According to the position and attitude data and the image coordinates of the homonymous points,the three-dimensional coordinates of the target point are calculated by space intersection. Finally,the results of space intersection is taken as the initial value and are overall optimized by the bundle adjustment. The experimental results show that the position information obtained by this method can achieve higher precision.
In recent years,smartphones have gradually integrated a variety of sensors in the rapid development process,including position sensors,attitude sensors such as magnetometers,accelerometers and digital cameras. At the same time,the advantages of small size and low cost provide the possibility to realize mobile image measurement. A new type of smartphone image measurement method is proposed through the platform of Android system and multi-sensor integrated by smartphones. The method firstly calibrates the smartphone camera to obtain the inner orientation elements,and develops the Android application program which can obtain the position and posture data of the mobile phone while acquiring the image data. Secondly,extraction,matching of feature points and error point deletion are performed on the image data. According to the position and attitude data and the image coordinates of the homonymous points,the three-dimensional coordinates of the target point are calculated by space intersection. Finally,the results of space intersection is taken as the initial value and are overall optimized by the bundle adjustment. The experimental results show that the position information obtained by this method can achieve higher precision.
引文
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[2]RAU J Y,HABIB A F,KERSTING A P,et al.Direct sensor orientation of a land-based mobile mapping system[J].Sensors,2011,11(7):7243-7261.
[3]尹邦杰,黄晓莹.浅析Android手机传感器机制及应用设计举例[J].计算机光盘软件与应用,2013(5):148-148.
[4]陈龙彪,李石坚,潘纲.智能手机,普适感知与应用[J].计算机学报,2015,38(2):423-438.
[5]THIBAUD M,GENEVES P,FOURATI H,et al.On attitude estimation with smartphones[C]∥Proceedings of 2017IEEE International Conference on Pervasive Computing and Communications.Kona:IEEE,2017:267-275.
[6]LIU T,ZHANG X,LI Q,et al.A visual-based approach for indoor radio map construction using smartphones[J].Sensors,2017,17(8):1790.
[7]KIM J,LEE S,AHN H,et al.Accuracy evaluation of a smartphone-based technology for coastal monitoring[J].Measurement,2013,46(1):233-248.
[8]DRUMMOND J.Manual of photogrammetry[J].Photogrammetric Record,2010,20(112):390-392.
[9]LI H,YANG D H,ZHAI C.Research on the pose measurement of a 6-DOF platform using a single camera[J].Optical Technique,2010,36(3):344-349.
[10]ZHANG Z Y.A flexible new technique for camera calibration[M].[S.l.]:IEEE Computer Society,2000.
[11]张勇,夏家莉,陈滨.Google Android开发技术[M].西安:西安电子科技大学出版社,2011:124-127.
[12]赵宏,郭立渌.手机内置加速度传感器数据的空间坐标转换算法[J].计算机应用,2016,36(2):301-306.
[13]张剑清,潘励,王树根.摄影测量学[M].2版.武汉:武汉大学出版社,2009:64-65.
[14]BAY H,ESS A,TUYTELAARS T,et al.Speeded-up robust features(SURF)[J].Computer Vision and Image Understanding,2008,110(3):346-359.
[15]MUJA M,LOWE D G.Fast approximate nearest neighbors with automatic algorithm configuration[C]∥Proceedings of the 4th International Conference on Computer Vision Theory and Application.Lisboa:DBLP,2009.
[16]FISCHLER M A,BOLLES R C.A paradigm for model fitting with applications to image analysis and automated cartography[J].Communication of the ACM,1981,24(6):381-395.
[17]AGARWAL S,SNAVELY N,SEITZ S M,et al.Bundle adjustment in the large[C]∥Proceedings of European Conference on Computer Vision.[S.l.]:SpringerVerlag,2010:29-42.
[18]NOCEDAL J,WRIGHT S J.Numerical optimization[M].[S.l.]:Springer,1999.