MRI: Acquisition of Light Detection and Ranging (LIDAR) Scanner for Computer Vision Research and Interdisciplinary Education

MRI：获取光探测和测距 (LIDAR) 扫描仪用于计算机视觉研究和跨学科教育

• 批准号: 1725057
• 负责人: Brittany Morago
• 金额: $ 11.9万
• 依托单位: University of North Carolina at Wilmington
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-01 至 2019-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1725057&HistoricalAwards=false
• 关键词: MRI; Acquisition; Light; Detection; Ranging

This project, acquiring a Leica ScanStation P30, aims to develop methods for aligning two dimensional (2D) and three dimensional (3D) data and to assemble educational tools using the produced 3D visualizations. The LIDAR (LIght Detection And Ranging) scanner will be used by professors and students studying and performing research in the fields of computer science, film, and art at the institution. The group builds on the researcher's existing work that creates navigable 3D environments from sets of 2D pictures and videos that are registered with 3D LIDAR scans. With the instrumentation this project would enable the following intertwined goals.(i) Build an interdisciplinary research group to further study how to describe and register multi-modality data, or data obtained with different cameras and sensors.(ii) Use the developed methods to build educational 3D applications with collaborators in film and history.(iii) Develop new, cross-disciplinary courses that use the proposed scanner to provide access for many students to the state-of-the-art technology.The developed courses would help the investigator train and recruit students for her research lab that can work on interdisciplinary projects.Although at present collecting and storing both 2D images and 3D LIDAR scans might be easier and more economical, fusing such multi-modality data remains challenging. Confusion is often created in automatic matching methods by the repetition and ambiguity that often occur in man-made scenes as well as the variety of properties on different renderings of the same subject. Image sets collected over a period of time during which lighting conditions and scene content may have changed, different artistic rendering, as well as varying sensor types (Camera, LIDAR, etc.), can all contribute to visual variations in data sets. However, by incorporating contextual information to visualize the regional properties that intuitively exist in each imagery source, the proponent has successfully addressed many of the obstacles. Her research group will also study how human perception can be used for registering 3D LIDAR data with other types of visual information.

该项目获得Leica ScanStation P30，旨在开发对齐二维（2D）和三维（3D）数据的方法，并使用生成的3D可视化组装教育工具。激光雷达（光探测和测距）扫描仪将用于教授和学生学习和执行计算机科学，电影和艺术领域的研究在该机构。该小组建立在研究人员现有工作的基础上，该工作从使用3D LIDAR扫描注册的2D图片和视频集创建可导航的3D环境。有了仪器，该项目将实现以下相互交织的目标。(i)建立一个跨学科的研究小组，进一步研究如何描述和注册多模态数据，或使用不同的相机和传感器获得的数据。(ii)使用开发的方法与电影和历史中的合作者一起构建教育3D应用程序。(iii)开发新的跨学科课程，使用拟议的扫描仪为许多学生提供最先进的技术。开发的课程将有助于研究人员为她的研究实验室培训和招募学生，这些学生可以从事跨学科项目。尽管目前收集和存储2D图像和3D LIDAR扫描可能更容易，更经济，但融合这种多模态数据仍然具有挑战性。由于人造场景中经常出现的重复和模糊性以及同一主题不同渲染效果上的各种属性，自动匹配方法经常会产生混乱。在一段时间内收集的图像集，在此期间照明条件和场景内容可能已经改变，不同的艺术渲染，以及不同的传感器类型（相机，激光雷达等），都可能导致数据集的视觉变化。然而，通过整合上下文信息来可视化每个图像源中直观存在的区域属性，支持者成功地解决了许多障碍。她的研究小组还将研究人类感知如何用于将3D LIDAR数据与其他类型的视觉信息进行配准。

项目成果

Photograph LIDAR Registration Methodology for Rock Discontinuity Measurement

• DOI: 10.1109/lgrs.2018.2817358
• 发表时间: 2018-06-01
• 期刊: IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
• 影响因子: 4.8
• 作者: Morago, Brittany;Bui, Giang;Duan, Ye
• 通讯作者: Duan, Ye

Point-based rendering enhancement via deep learning

• DOI: 10.1007/s00371-018-1550-6
• 发表时间: 2018-05
• 期刊: The Visual Computer
• 作者: Giang Bui;Truc Le;Brittany Morago;Y. Duan