OdoViz is a reactive web-based tool for 3D visualization and processing of autonomous vehicle datasets designed to support common tasks in visual place recognition research. The system includes functionality for loading, inspecting, visualizing, and processing GPS/INS poses, point clouds and camera images. It supports a number of commonly used driving datasets and can be adapted to load custom datasets with minimal effort. OdoViz's design consists of a slim server to serve the datasets coupled with a rich client frontend. This design supports multiple deployment configurations including single user stand-alone installations, research group installations serving datasets internally across a lab, or publicly accessible web-frontends for providing online interfaces for exploring and interacting with datasets. The tool allows viewing complete vehicle trajectories traversed at multiple different time periods simultaneously, facilitating tasks such as sub-sampling, comparing and finding pose correspondences both across and within sequences. This significantly reduces the effort required in creating subsets of data from existing datasets for machine learning tasks. Further to the above, the system also supports adding custom extensions and plugins to extend the capabilities of the software for other potential data management, visualization and processing tasks. The platform has been open-sourced to promote its use and encourage further contributions from the research community.
翻译:OdoViz是一个基于网络的3D可视化和处理自动车辆数据集的被动工具,旨在支持视觉化识别研究的共同任务。该系统包括装装、检查、可视化和处理全球定位系统/INS配置、点云和相机图像的功能。它支持一些常用的驱动数据集,可以尽量不费力地将数据集装上自定义数据集。OdoViz的设计包括一个微薄的服务器,为数据集服务,同时提供丰富的客户前端。这一设计支持多种部署配置,包括单个用户独立装置、为实验室内部数据集提供内部服务的研究组装置,或向公众开放的网络前端,以提供在线界面,用于与数据集进行探索和互动。该工具允许同时查看多个不同时期的完整车辆轨迹,便于分集、比较和查找跨序列和在内部的相形对等任务。这大大降低了从现有数据集中创建数据分组以完成机器学习任务所需的努力。此外,该系统还支持增加定制的扩展用户扩展和插件,以便利用其视觉分析平台,从而推动其视觉管理潜力。