Conference Paper

Proceedings of SimBuild Conference 2024

Decomposition of Dynamic Window Views Using Semantic Segmentation

Simeon Nyambaka Ingabo, Ying-Chieh Chan
National Taiwan University, Taiwan

Abstract: Movement in window views impacts the indoor experience and comfort of building occupants. Some building standards therefore stipulate the presence of dynamic content as a key window view quality evaluation criterion. However, there is a scarcity of tools for evaluation of dynamic window views, owing to the complex interactions between elements in the views. Computing the compositional ratios of view elements vis-à-vis the amount of movement demands an integrated methodological framework. This paper therefore addresses the insufficiency of existing literature on dynamic window view evaluation tools and methods. A framework was developed using the DeepLabV3 semantic segmentation architecture pre-trained on the Cityscapes dataset, for decomposition of dynamic content in fifty recorded urban window views. Movement within the views was calculated using functions contained in the OpenCV library. The pre-trained model yielded accurate predictions of twenty Cityscapes urban object classes, thus facilitating calculation of compositional ratios in the window views. A case study was also discussed to illustrate the practical application of the framework in determination of preferred amount of movement in office window views. This study affirms the suitability of semantic segmentation as a dynamic window view content evaluation tool.
Keywords: Dynamic window views, Semantic segmentation, Window view composition
Pages: 830 - 837
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