3D Scene Reconstruction Based on Multi-source Sensor Data Fusion

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3D Scene Reconstruction Based on Multi-source Sensor Data Fusion

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[1]Chen Yifei,Guo Sheng,Pan Wenan,et al.3D Scene Reconstruction Based on Multi-source Sensor Data Fusion[J].Journal of Zhengzhou University (Engineering Science),2021,42(02):81-87.[doi:10.13705/j.issn.1671-6833.2021.02.008]

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Journal of Zhengzhou University (Engineering Science)[ISSN 1671-6833/CN 41-1339/T] Volume: 42卷 Number of periods: 2021 02 Page number: 81-87 Column: Public date: 2021-04-12

Title:: 3D Scene Reconstruction Based on Multi-source Sensor Data Fusion

Author(s):: Chen Yifei; Guo Sheng; Pan Wen’an; Lu Yanhui;; School of Information Engineering, Zhengzhou University; Chinese University of Hong Kong (Shenzhen) Institute of Technology; Shenzhen Institute of Data;

Keywords:: data fusion; 3D modeling; deep learning; object detection; feature matching; scene recurrence

CLC:: -

DOI:: 10.13705/j.issn.1671-6833.2021.02.008

Abstract:: Aiming at the target redundancy in reconstruction of certain scenes, in this paper a data fusion method of the camera RGB bitmap and lidar data was employed to solve the problem. In the field of 3D reconstruction, this method of data fusion could eliminate the irrelevant targets in the specific scene and reproduce the three-dimensional scene. The lightweight LeGO-LOAM algorithm was used to extract and match different types of feature points at first, and point clouds were merged at different times to complete the reproduction of the point cloud map. For the irrelevant targets in the constructed point cloud map, with the help of multi-source sensor data and deep learning application technology in the field of computer vision, object detection and elimination are accomplished in three-dimensional space. For the two different processes of point cloud modeling and target detection, the method of point cloud registration was adopted to fuse the algorithm and finally complete the scene reproduction in the campus environment. Experimental results showed that the method based muti-source data fusion could effectively combine the two processes of 3D modeling and object detection. The method proposed in this paper could be applied to smart cities, unmanned driving and other fields, and should have practical application value.

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