In this paper,one of the key elements of intelligent data processing in digital photogrammetry is discussed based on machine vision:efficient management technology of massive point cloud,an improved algorithm for hash mapping 3D data on GPU is proposed.The algorithm can efficiently perform dynamic insertion,update and indexing of data without the limitation of data scale.We applied the algorithm to TSDF (truncated signed distance field) algorithm for point cloud fusion,which can reduce the noise of single frame and the data registration error between different frames in a very efficient way.Currently,most of the data structures of point cloud fusion algorithms are regular or hierarchical grid data structures,so the object bounding boxes should be specified in advance.Moreover,the hierarchical data structure is complex and hard to parallelization.Therefore,the requirements of dynamic scalability,updating and indexing data of real-time 3D reconstruction cannot be satisfied.This paper exploited hash map to manage 3D data.At the same time,the current active region could be estimated with sensor motion to exchange data between host and GPU,keeping low memory utilization of GPU.In the experiments on different levels of graphics cards(GTX960,GTX1050,GTX1060),the algorithm can satisfy the real-time frame rate requirements(60 fps,2.11×105 points per frame),so it meets the requirement of efficient management of 3D point cloud data in three-dimensional imaging.
ZHENG Shunyi
,
HE Yuan
,
XU Gang
,
WANG Chen
,
ZHU Fengbo
. Hash Map Method of 3D Point Cloud Data for Real-time Organizing[J]. Acta Geodaetica et Cartographica Sinica, 2018
, 47(6)
: 825
-832
.
DOI: 10.11947/j.AGCS.2018.20170619
[1] 郑顺义, 周漾, 黄荣永, 等. 馆藏文物三维测量与重建方法研究[J]. 测绘科学, 2014, 39(7):76-79. ZHENG Shunyi, ZHOU Yang, HUANG Rongyong, et al. A Method of 3D Measurement and Reconstruction for Cultural Relics in Museums[J]. Science of Surveying and Mapping, 2014, 39(7):76-79.
[2] 翟瑞芳, 张剑清. 基于激光扫描仪的点云模型的自动拼接[J]. 地理空间信息, 2004, 2(6):37-39. ZHAI Ruifang, ZHANG Jianqing. Automatic Registration of Point Clouds Based on Laser Scanner[J]. Geospatial Information, 2004, 2(6):37-39.
[3] RUSINKIEWICZ S, HALL-HOLT O, LEVOY M. Real-time 3D Model Acquisition[J]. ACM Transactions on Graphics (TOG), 2002, 21(3):438-446.
[4] ROSSIGNAC J, BORREL P. Multi-resolution 3D Approximations for Rendering Complex Scenes[C]//FALCIDIENO B, KUNⅡ T L. Modeling in Computer Graphics. Berlin, Heidelberg:Springer, 1993:455-465.
[5] CURLESS B, LEVOY M. A Volumetric Method for Building Complex Models from Range Images[C]//Proceedings of the 23rd Annual Conference on Computer Graphics and Interactive Techniques.[S.l.]:ACM, 1996:303-312.
[6] NEWCOMBE R A, IZADI S, HILLIGES O, et al. Kinect-Fusion:Real-time Dense Surface Mapping and Tracking[C]//Proceedings of the 10th IEEE International Symposium on Mixed and Augmented Reality. Basel, Switzerland:IEEE, 2011:127-136.
[7] IZADI S, KIM D, HILLIGES O, et al. KinectFusion:Real-time 3D Reconstruction and Interaction Using a Moving Depth Camera[C]//Proceedings of the 24th Annual ACM Symposium on User Interface Software and Technology. Santa Barbara, California:ACM, 2011:559-568.
[8] 谭歆. KinectFusion三维重建的再优化[D]. 杭州:浙江大学, 2015. TAN Xin. Global Optimization for 3D Reconstruction Based on KinectFusion[D]. Hangzhou:Zhejiang University, 2015.
[9] WHELAN T, MCDONALD J, KAESS M, et al. Kintinuous:Spatially Extended Kinectfusion[R]. Cambridge:MIT, 2012.
[10] WHELAN T, JOHANNSSON H, KAESS M, et al. Robust Real-time Visual Odometry for Dense RGB-D Mapping[C]//Proceedings of 2013 IEEE International Conference on Robotics and Automation. Karlsruhe, Germany:IEEE, 2013:5724-5731.
[11] ROTH H, VONA M. Moving Volume KinectFusion[C]//Proceedings of the British Machine Vision Conference. Boston, MA:BMVA Press, 2012:1-11.
[12] ZENG Ming, ZHAO Fukai, ZHENG Jiaxiang, et al. Octree-based Fusion for Realtime 3D Reconstruction[J]. Graphical Models, 2013, 75(3):126-136.
[13] ZENG Ming, ZHAO Fukai, ZHENG Jiaxiang, et al. A Memory-efficient Kinectfusion Using Octree[M]//Proceedings of the 1st International Conference on Computational Visual Media. Beijing, China:Springer, 2012:234-241.
[14] CHEN Jiawen, BAUTEMBACH D, IZADI S. Scalable Real-time Volumetric Surface Reconstruction[J]. ACM Transactions on Graphics (TOG), 2013, 32(4):113.
[15] KÄMPE V, SINTORN E, ASSARSSON U. High Resolution Sparse Voxel Dags[J]. ACM Transactions on Graphics (TOG), 2013, 32(4):101.
[16] NIEβNER M, ZOLLHÖFER M, IZADI S, et al. Real-time 3D Reconstruction at Scale Using Voxel Hashing[J]. ACM Transactions on Graphics (TOG), 2013, 32(6):169.
[17] KLINGENSMITH M, DRYANOVSKI I, SRINIVASA S, et al. Chisel:Real Time Large Scale 3D Reconstruction Onboard a Mobile Device Using Spatially-Hashed Signed Distance Fields[C]//Proceedings of Robotics:Science and Systems. Rome, Italy:[s.n.], 2015:4.
[18] TESCHNER M, HEIDELBERGER B, MVLLER M, et al. Optimized Spatial Hashing for Collision Detection of Deformable Objects[C]//Proceedings of the 8th Workshop on Vision, Modeling, and Visualization. Munich, Germany:AKA, 2003:47-54.
[19] RIVEST R. The MD5 Message-digest Algorithm[R]. Request for Comments 1321 Cambridge:MIT Laboratory for Computer Science and RSA Data Security, Inc, 1992.
[20] TUBIC D, HÉBERT P, LAURENDEAU D. A Volumetric Approach for Interactive 3D Modeling[J]. Computer Vision and Image Understanding, 2003, 92(1):56-77.
[21] TUBIC' D, HÉBERT P, LAURENDEAU D. 3D Surface Modeling from Curves[J]. Image and Vision Computing, 2004, 22(9):719-734.
[22] WERNER D, AL-HAMADI A, WERNER P. Truncated Signed Distance Function:Experiments on Voxel Size[C]//Proceedings of the 11th International Conference Image Analysis and Recognition. Cham:Springer, 2014:357-364.
[23] 王攀. 基于Out-of-Core的海量数据等值面绘制技术研究与实现[D]. 长沙:国防科学技术大学, 2008. WANG Pan. Research on Isosurface Extraction of Large Scale Datasets With Out-of-core Method[D]. Changsha:National University of Defense Technology, 2008.
[24] DESCHÊNES J D, HÉBERT P, LAMBERT P, et al. Multiresolution Interactive Modeling with Efficient Visualization[C]//Proceedings of the 5th International Conference on 3-D Digital Imaging and Modeling. Ottawa, Ontario, Canada:IEEE, 2005:39-46.
[25] ZWICKER M, PFISTER H, VAN BAAR J, et al. Surface splatting[C]//Proceedings of the 28th Annual Conference on Computer Graphics and Interactive Techniques. Los Angeles:ACM, 2001:371-378.
[26] LORENSEN W E, CLINE H E. Marching Cubes:A High Resolution 3D Surface Construction Algorithm[J]. ACM SIGGRAPH Computer Graphics, 1987, 21(4):163-169.
