用于交互式视觉设计优化的顺序图库
Sequential Gallery for Interactive Visual Design Optimization
摘要：
可视化设计任务通常涉及调整许多设计参数。例如，照片的颜色分级涉及许多参数，其中一些非专家用户可能不熟悉。我们提出了一种新的用户在循环优化方法，允许用户有效地找到一个合适的参数集，通过更容易的二维搜索子任务探索这样一个高维的设计空间。这种方法被称为顺序平面搜索，它基于贝叶斯优化，使用户尽可能少地进行必要的查询。为了帮助用户响应平面搜索查询，我们还建议使用基于图库的界面，该界面提供在自适应网格视图中排列的二维子空间中的选项。我们称这个交互式框架为顺序画廊，因为用户顺序地从界面提供的选项中选择最佳选项。我们的合成函数的实验表明，我们的顺序平面搜索可以找到令人满意的解决方案，在更少的迭代比基线。我们还进行了初步的用户研究，结果表明，新手可以有效地完成搜索任务与顺序画廊在照片增强的情况下。
英文摘要：
Visual design tasks often involve tuning many design parameters. For example, color grading of a photograph involves many parameters, some of which non-expert users might be unfamiliar with. We propose a novel user-in-the-loop optimization method that allows users to efficiently find an appropriate parameter set by exploring such a high-dimensional design space through much easier two-dimensional search subtasks. This method, called sequential plane search, is based on Bayesian optimization to keep necessary queries to users as few as possible. To help users respond to plane-search queries, we also propose using a gallery-based interface that provides options in the two-dimensional subspace arranged in an adaptive grid view. We call this interactive framework Sequential Gallery since users sequentially select the best option from the options provided by the interface. Our experiment with synthetic functions shows that our sequential plane search can find satisfactory solutions in fewer iterations than baselines. We also conducted a preliminary user study, results of which suggest that novices can effectively complete search tasks with Sequential Gallery in a photo-enhancement scenario.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
