Point Cloud Identification of Joints in Tunnel Faces and Its Implementation in a Microservice

Quickly identifying discontinuity of the rock in a tunnel face and interpreting its geometric and mechanical parameters are considered as important basis for realizing remote tunnel diagnosis. However, 3D point cloud recognition based on digital photos often relies on commercial programs. Based on the open source framework of AliceVision, this paper developed a microservice module for point cloud information recognition of discontinuity of rocks in a tunnel face. Encapsulated with the Django framework, the module can be flexibly deployed in a platform that supports the microservice architecture. With photos of the rock mass on the tunnel face taken from different perspectives and uploaded remotely by users, the microservice helps automatically identify 3D point cloud and achieve 3D reconstruction. Currently, the microservice module has been deployed infrastructure Smart Service System（iS3）developed by Tongji University. The results compared with those obtained from other software show that the microservice module can meet the basic need for 3D construction with advantage in the computational speed although effort is still needed to further improve the accuracy.