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浙江大学学报(工学版)
计算机技术﹑电信技术     
基于全景相机和全向激光雷达的致密三维重建
杨力, 刘俊毅, 王延长, 刘济林
浙江大学 信息与电子工程学系,浙江 杭州 310027
3D dense reconstruction based on omnidirectional camera and laser range finder
YANG Li, LIU Jun-yi, WANG Yan-chang, LIU Ji-lin
Department of Information Science and Electronic Engineering, Zhejiang University, Hangzhou 310027, China
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摘要:

为了实现360°全景三维重建,提出一种基于全景相机和全向激光雷达的联合标定和数据融合方法.采用二维平面靶标进行联合标定,克服传统方法中提取雷达数据边缘信息不精确导致的误差,并且标定过程简单.在此基础上,提出一种基于超像素分割的致密三维重建算法,得到与物体平面一致的超像素块分割结果,根据超像素块内三维点估算物体平面,推算每个像素的深度信息,得到致密的三维重建信息.结果表明,该算法标定结果精确,三维重建景物轮廓清晰,色彩对应准确.

Abstract:

To produce the 360-degree three dimensional reconstruction, a calibration and data fusion methods were proposed based on omnidirectional camera and laser range finder. Using the 2D checkerboard for joint calibration, our method doesn’t rely on the edge information of the lidar data, thus avoids the error of feature extraction. We also proposed a dense 3D reconstruction method based on superpixel. First, an image is segmented into superpixel blocks, then the plane of the block is estimated based on the lidar data, and last the depth information of each pixel in the superpixel block is calculated. As the experimental results show, the calibration is accurate, the contour of the scene is clear and the mapping of the color is correct.

出版日期: 2014-08-01
:  TP 391.4  
基金资助:

国家自然科学基金资助项目(60534070,90820306).

通讯作者: 刘济林,男,教授     E-mail: liujl@zju.edu.cn
作者简介: 杨力(1979—),男,博士生,从事机器视觉研究.E-mail: larryy@zju.edu.cn
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引用本文:

杨力, 刘俊毅, 王延长, 刘济林. 基于全景相机和全向激光雷达的致密三维重建[J]. 浙江大学学报(工学版), 10.3785/j.issn.1008-973X.2014.08.018.

YANG Li, LIU Jun-yi, WANG Yan-chang, LIU Ji-lin. 3D dense reconstruction based on omnidirectional camera and laser range finder. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 10.3785/j.issn.1008-973X.2014.08.018.

链接本文:

http://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2014.08.018        http://www.zjujournals.com/eng/CN/Y2014/V48/I8/1481

[1] ZHANG Q, PLESS R. Fusing video and sparse depth data in structure from motion[C]∥ IEEE International Conference on Image Processing(ICIP). Singapore: IEEE, 2004: 3403-3406.
[2] MAIER D, BENNEWITZ M, STACHNISS C. Self-supervised obstacle detection for humanoid navigation using monocular vision and sparse laser data[C]∥ IEEE International Conference on Robotics and Automation (ICRA). Shanghai, China: IEEE,2011: 1263-1269.
[3] SUNG C H, CHUNG M J. Dense scene 3D reconstruction using color based sampling with fusion of image and sparse laser[C]∥ IEEE 17th Korea-Japan Joint Workshop on Frontiers of Computer Vision (FCV). Ulsan: 2011: 16.
[4] BRIM X, GOULETTE F. Modeling and Calibration of coupled fish-eye CCD camera and laser range scanner for outdoor environment reconstruction[C]∥ IEEE Sixth International Conference on 3-D Digital Imaging and Modeling (3DIM). Montreal, Canada: IEEE, 2007: 320-327.
[5] ZHANG Q, PLESS R. Extrinsic calibration of a camera and laser range finder (improves camera calibration)[C]∥ IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Sendai, Japan: IEEE,2004: 2301-2306.
[6] LI G, LIU Y. An algorithm for extrinsic parameters calibration of a camera and a laser range finder using line features[C]∥ IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). San Diego, CA: IEEE,2007: 3854-3859.
[7] RODRIGUEZ F, FREMONT S, BONNIFAIT P. Extrinsic calibration between a multi-layer lidar and a camera[C]∥ IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems. Seoul,Korea: IEEE,2008: 214-219.
[8] 项志宇,郑路.摄像机与3D激光雷达联合标定的新方法.浙江大学学报:工学版.[J]. 2009. 43(8): p. 1401-1405.
XIANG Z, ZHENG L. Novel joint calibration method of camera and 3D laser range finder[J]. Journal Of Zhejiang University: Engineering Science, 2009, 43(8): 1401-1405.
[9] SCARAMUZZA D, HARATI A, SIEGWART R. Extrinsic self calibration of a camera and a 3d laser range finder from natural scenes[C]∥ Ieee/rsj International Conference on Intelligent Robots and Systems (IROS). San Diego: IEEE, 2007: 4164-4169.
[10] 彭骏驰,唐进,王力,等.激光雷达与摄像机的配准[J].微计算机信息,2008, 24(4): 46.
PENG Jun-chi, TANG Jin, WANG Li, et al. Regis tration of laser range finder and camera [J]. Microcomputer Information. 2008, 24: 46.
[11] Velodyne acoustics, inc. High definition lidar hdl-64e s2 [EB/OL]. Http:∥www.velodyne.com/lidar.
[12] DIEBEL J, THRUN S. An application of markov random fields to range sensing[C]∥ Proceedings of Conference on Neural Information (nips). Whistler: the mit press, 2005.
[13] Point grey research, inc. High resolution ladybug 3 spherical digital video camera system[EB/OL]. Http:∥www.ptgrey.com/products/ladybug3.
[14] COMANICIU D, MEER P, MEAN S. A robust approach toward feature space analysis [J]. Ieee Transactions on Pattern Analysis and Machine Intelligence (pami), 2002. 24(5): 603-619.
[15] FERNAND M. Topographic distance and watershed lines [J]. Signal Processing, 1994. 38(1): 113-125.
[16] SHI J, MALIK J. Normalized cuts and image segmentation [J]. Ieee Transactions on Pattern Analysis and Machine Intelligence (pami), 2000, 22(8): 888-905.
[17] LIU M. Entropy rate superpixel segmentation[C]∥ Ieee Conference on Computer Vision and Pattern Recognition (cvpr). Providence: ieee, 2011: 2097-2104

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