|
- 2018
低成本大视场深度相机阵列系统
|
Abstract:
在测距传感器不断轻量化、小型化以及室内外地图一体化导航应用的驱动下,三维(3D)室内移动测量成为当今研究和应用的热点,在室内建模、室内定位等新兴领域中的应用越来越广泛。3D室内移动测量系统通常配备激光扫描仪、全景相机、惯性测量单元(inertial measurement unit,IMU)系统和里程计等传感器,虽能实现3D室内点云数据的采集,但其距离传感器-激光扫描仪价格昂贵且便携性较差。彩色深度(RGB depth,RGB-D)相机为低成本3D室内移动测量系统构建提供了新的距离成像传感器选择,但主流型号RGB-D相机视场角小,继而导致数据采集效率远低于传统激光扫描仪,难以做到点云数据的完整覆盖与稳健采集,且易造成同时定位与制图(simultaneous localization and mapping,SLAM)过程中跟踪失败。针对以上问题,构建了一种低成本室内3D移动测量系统采集设备,通过组合多台消费级RGB-D相机构成大视场RGB-D相机阵列,提出了一种阵列RGB-D相机内外参数标定方法,并通过实验检验了设计系统采集的点云数据的精度
[1] | Sarbolandi H, Lefloch D, Kolb A. Kinect Range Sensing:Structured-Light Versus Time-of-Flight Kinect[J]. <em>Computer Vision and Image Understanding</em>, 2015, 139:1-20 |
[2] | Zhang Z. A Flexible New Technique for Camera Calibration[J]. <em>Pattern Analysis and Machine Intelligence</em>, 2000, 22(11):1330-1334 |
[3] | Zhang Yongjun, Hu Binghua, Zhang Jianqing. Absolute Orientation of Large Rotation Angle Images[J].<em>Geomatics and Information Science of Wuhan University</em>, 2010,35(4):427-431(张永军, 胡丙华, 张剑清. 大旋角影像的绝对定向方法研究[J]. 武汉大学学报·信息科学版, 2010,35(4):427-431) |
[4] | Zhu Xinyan, Zhou Chenghu, Guo Wei, et al. Preliminary Study on Conception and Key Technologies of the Location-Based Pan-Information Map[J]. <em>Geomatics and Information Science of Wuhan University</em>, 2015, 40(3):285-295(朱欣焰, 周成虎, 呙维,等. 全息位置地图概念内涵及其关键技术初探[J]. 武汉大学学报·信息科学版, 2015, 40(3):285-295) |
[5] | Sheng Dexin, Yang Zhenqiu. Construction of Geometric Models of Ancient Buildings Based on Laser Point Cloud Data[J]. <em>Engineering of Surveying and Mapping</em>, 2015,24(7):76-80(盛德新, 杨振球. 基于激光点云数据的古建筑BIM几何模型构建[J]. 测绘工程, 2015,24(7):76-80) |
[6] | Sharma P, Joshi R P,Boby R A, et al. Projectable Interactive Surface Using Microsoft Kinect V2:Recovering Information from Coarse Data to Detect Touch[C]. 2015 IEEE/SICE International Sympo-sium on System Integration (SⅡ), Aichi, Japan, 2015 |
[7] | Yang S, Yi X, Wang Z, et al. Visual SLAM Using Multiple RGB-D Cameras[C]. IEEE International Conference on Robotics and Biomimetics, Zhuhai, China, 2015 |
[8] | Pan Yixiao. Study of 3D Model Reconstruct Technology Based on Range Image Data[D]. Changsha:Central South University, 2014(潘一潇. 基于深度图像的三维建模技术研究[D]. 长沙:中南大学, 2014) |
[9] | Corti A, Giancola S, Mainetti G, et al. A Metrolo-gical Characterization of the Kinect V2 Time-of-Flight Camera[J]. <em>Robotics & Autonomous Systems</em>, 2016, 75:584-594 |
[10] | Fankhauser P,Bloesch M, Rodriguez D, et al. Kinect V2 for Mobile Robot Navigation:Evaluation and Modeling[C]. International Conference on Advanced Robotics, Istanbul, Turkey, 2015 |
[11] | Jiménez D, Pizarro D,Mazo M, et al. Modeling and Correction of Multipath Interference in Time of Flight Cameras[J]. <em>Image and Vision Computing</em>, 2014, 32(1):1-13 |
[12] | Labbe M, Michaud F. Appearance-Based Loop Closure Detection for Online Large-Scale and Long-Term Operation[J]. <em>IEEE Transactions on Robo-tics</em>, 2013, 29(3):734-745 |
[13] | Lin Yaodong. 3D Surface Modeling of Remanufactured Based on Kinect[D]. Harbin:Harbin Institute of Technology, 2015(林耀冬. 基于Kinect的再制造零件三维表面建模系统[D]. 哈尔滨:哈尔滨工业大学, 2015) |
[14] | Ju Xuan. Joint Depth and Color Camera Calibration and Its Application in Augmented Reality[D]. Hang-zhou:Zhejiang University, 2014(琚旋. 深度与彩色相机的联合标定及其在增强现实中的应用[D]. 杭州:浙江大学, 2014) |
[15] | Lachat E, Macher H, Mittet M A, et al. First Experiences with Kinect V2 Sensor for Close Range 3D Modelling[J]. <em>The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences</em>, 2015, 40(5):93-98 |
[16] | Wu Nailiang, Yan Fei, Bu Chunguang. Mobile Robot 3D Environment Reconstruction Based on Visual Odemeter[J]. <em>J</em> <em>Huazhong Univ of Sci & Tech (Natural Science Edition)</em>, 2015, 43(S1):337-340(吴乃亮,闫飞,卜春光. 基于视觉里程计的移动机器人三维场景重构[J]. 华中科技大学学报(自然科学版), 2015, 43(S1):337-340) |
[17] | Labbé M, Michaud F. Memory Management for Real-Time Appearance-Based Loop Closure Detection[C]. IEEE/RSJ International Conference on Intelligent Robots and Systems, San Francisco, USA, 2011 |
[18] | Labbé M, Michaud F. Online Global Loop Closure Detection for Large-Scale Multi-session Graph-Based SLAM[C]. IEEE/RSJ International Confe-rence on Intelligent Robots and Systems, Chicago, USA, 2014 |
[19] | Yu Jianwei, Wei Chi. SLAM Based Indoor Mobile Mapping System and Application[J]. <em>Bulletin of Surveying and Mapping</em>, 2016(6):146-147(余建伟,危迟. 基于SLAM的室内移动测量系统及其应用[J]. 测绘通报, 2016(6):146-147) |
[20] | Zhang Yun, Yin Lu, Wang Yuting, et al. Real-Time Visual Odometry System Based on Sift GPU[J]. <em>Journal of Terahertz Science and Electronic Information Technology,</em> 2015,13(6):897-902(张云, 尹露, 王雨婷, 等. 基于Sift GPU特征匹配方法的实时视觉里程计系统[J]. 太赫兹科学与电子信息学报, 2015,13(6):897-902) |
[21] | Zhang Yi, Tong Xuerong, Luo Yuan. A Novel Monocular Visual Odometry Method Based on Improved SURF Algorithm[J]. <em>Journal of Chongqing University of Posts and Telecommunications(Na-tural Science Edition)</em>, 2014(3):390-396(张毅,童学容,罗元. 一种改进SURF算法的单目视觉里程计[J]. 重庆邮电大学学报(自然科学版), 2014(3):390-396) |