Category 3DMMAI

3DMMAI: Utility Semantic Segmentation Network

Authors: Maryam Jameela, Gunho Sohn, Sunghwan Yon Department of Earth and Space Science and Engineering, York University Toronto, ON M3J 1P3 Canada The 3DMMAI pipeline includes several stages of post-data acquisition processing, and the significant step is the semantic segmentation…

ICAR 2021 RPV SLAM (3DMMAI) Paper Accepted

Dr. Jungwon Kang, Dr Yujia Zhang and Zhen Liu (2nd Year PhD Student) in the lab published their paper on RPV-SLAM: Range-augmented Panoramic Visual SLAM for Mobile Mapping System with Panoramic Camera and Tilted LiDAR in the the 20th International Conference on…

Welcome New Project Coordinator, Ms. Mercedes Boateng

Ms. Mercedes Boateng joined our lab from September 10th, 2020 as a project coordinator. Mercedes will contribute to our ongoing research projects as the project coordinator, particularly for 3D Mobile Mapping Artificial Intelligence (3DMMAI) project and Intelligent Systems for Sustainable Urban…

3DMMAI: Semantic Segmentation

The next natural step of the pipeline for scene understanding and classification is semantic segmentation, which labels every point and pixel in the point cloud and image respectively of their enclosing object or region. There are multiple existing deep neural…

3DMMAI: Noise Filtering

The 3DMMAI pipeline includes several stages of post data acquisition processing, and the first significant step is noise filtering. LiDAR (Light Detection and Ranging) mounted with static and mobile vehicles has been rapidly adopted as a primary sensor for mapping…

3D Mobile Mapping AI Project

3D Mobile Mapping AI (3DMMAI) Project 3D Mobile Mapping AI Project is a collaborative large-scale research program supported by Teledyne Optec Inc and the NSERC Collaborative Research Development (CRD) Program. A total of $2.6M cash and in-kind contribution will be…