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AverageExplorer: Interactive Exploration and Alignment of Visual Data Collections

机译:AverageExplorer:交互式探索和对齐可视数据集合

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This paper proposes an interactive framework that allows a userrnto rapidly explore and visualize a large image collection using thernmedium of average images. Average images have been gainingrnpopularity as means of artistic expression and data visualization, butrnthe creation of compelling examples is a surprisingly laborious andrnmanual process. Our interactive, real-time system provides a way tornsummarize large amounts of visual data by weighted average(s) ofrnan image collection, with the weights reflecting user-indicated importance.rnThe aim is to capture not just the mean of the distribution,rnbut a set of modes discovered via interactive exploration. We posernthis exploration in terms of a user interactively “editing” the averagernimage using various types of strokes, brushes and warps, similar torna normal image editor, with each user interaction providing a newrnconstraint to update the average. New weighted averages can bernspawned and edited either individually or jointly. Together, theserntools allow the user to simultaneously perform two fundamentalrnoperations on visual data: user-guided clustering and user-guidedrnalignment, within the same framework. We show that our system isrnuseful for various computer vision and graphics applications.
机译:本文提出了一个交互式框架,该框架允许用户使用平均图像媒介快速浏览和可视化大型图像集合。普通图像作为艺术表达和数据可视化的手段已广受欢迎,但是创建引人注目的示例却是一个令人费力的手工过程。我们的交互式实时系统提供了一种方法,可以通过rnan图像集合的加权平均值汇总大量的可视数据,其权重反映了用户指示的重要性。通过互动探索发现的一组模式。我们通过用户使用各种类型的笔触,画笔和扭曲交互式“编辑”平均图像的方式来进行这种探索,类似于普通图像编辑器,每个用户交互都提供了更新平均数的新约束。可以单独或联合产生新的加权平均值并进行编辑。在一起,这两个工具使用户可以在同一框架内同时对视觉数据执行两个基本操作:用户引导的聚类和用户引导的对齐。我们证明了我们的系统对于各种计算机视觉和图形应用都没有用。

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