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3DLIVE Techinque Analysis: A Study of Segmentation, Classification and Object Detection of 3D Point Cloud Datasets.
| 题名： | 3DLIVE Techinque Analysis: A Study of Segmentation, Classification and Object Detection of 3D Point Cloud Datasets. |
| 作者： | Moquin, D; Thorpe, C; Williams, C; Schwartz, C; Turk, D; Emad, A. |
| 摘要： | The aim of this research is to discuss the current state-of-the-art practices and methods for machine learning algorithms thatperform on point cloud data. The research conducted will be applied to the in-house efforts of the Three Dimensional LidarVisualization and Exploitation (3DLIVE) team, whose primary goal is to create a new system for visualization and interactionwith point cloud data for Target Coordinate Mensuration (TCM). The proposed machine learning methods relate to three maintopics in machine learning for 3D point clouds and computer vision, each of which had its own segment of papers researched.These topics are segmentation, classification and object detection, and the selected papers are of recent studies that achievedstate-of-the-art performances. The findings of this research are a select few methods that show the most promising results andeffectiveness to the 3DLIVE team. Effectiveness is largely dependent on the scalability and applicability of the algorithm to the3DLIVE use case as well as its accuracy and precision. |
| 总页数： | 49 pages |
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