We present ReViVD, a tool for exploring and filtering large trajectory-based datasets using virtual reality. ReViVD's novelty lies in using simple 3D shapes -- such as cuboids, spheres and cylinders -- as queries for users to select and filter groups of trajectories. Building on this simple paradigm, more complex queries can be created by combining previously made selection groups through a system of user-created Boolean operations. We demonstrate the use of ReViVD in different application domains, from GPS position tracking to simulated data (e.g., turbulent particle flows and traffic simulation). Our results show the ease of use and expressiveness of the 3D geometric shapes in a broad range of exploratory tasks. ReViVD was found to be particularly useful for progressively refining selections to isolate outlying behaviors. It also acts as a powerful communication tool for conveying the structure of normally abstract datasets to an audience.
翻译:我们展示了ReVIVD, 这是一种利用虚拟现实探索和过滤大型轨道数据集的工具。 ReVIVD的新颖之处在于使用简单的 3D 形状 -- -- 如幼崽、球体和圆柱体 -- -- 作为用户选择和筛选轨迹组的查询。在这个简单范例的基础上,通过一个用户创建的布林操作系统,将先前的筛选组组合起来,可以产生更复杂的查询。我们展示了在从全球定位系统定位跟踪到模拟数据(例如动荡粒子流和流量模拟)的不同应用领域使用REVVD。我们的结果显示,在广泛的探索任务中,3D 几何形状的使用和清晰度十分容易。 ReVVD被认为特别有助于逐步改进选择,从而分离出外表的行为。它还作为一种强大的通信工具,将通常的抽象数据集的结构传递给观众。