Exposure to environmental changes in windows are essential to sustain healthy conditions indoors; however, there are no procedures for capturing these variations dynamically. In this study, we provide the foundations for building a framework aimed at understanding the effects of luminous variability in window views. First, we labelled a sample of views (n = 40) using a surface layout approach, resulting in four view type categories. Next, we captured time-lapse imagery from selected views (n = 8) to produce panorama sequences. We calculated the absolute lightness variation in Matlab, resulting in three luminous change categories (i.e. Global, Local, and Minimal variation). Concurrently, we collected environmental measures to define variability thresholds. The integrated analysis showed a higher occurrence of luminous changes in two categories in controlled conditions, suggesting that viewing configuration might prevail over window orientation for conveying light changes over time.

中文翻译：

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评估窗户视图中的日光变化：分类和捕捉动态户外场景的系统程序

暴露在窗户中的环境变化对于维持室内健康状况至关重要；但是，没有动态捕获这些变化的过程。在这项研究中，我们为构建一个框架提供了基础，该框架旨在了解窗口视图中光变化的影响。首先，我们使用表面布局方法标记了一个视图样本 (n = 40)，从而产生了四个视图类型类别。接下来，我们从选定的视图 (n = 8) 中捕获延时图像以生成全景序列。我们在 Matlab 中计算了绝对亮度变化，产生了三个亮度变化类别（即全局、局部和最小变化）。同时，我们收集了环境措施来定义可变性阈值。