Publication | Conference on Computer-Supported Cooperative Work and Social Computing 2020

Socio-Spatial Comfort

Using Vision-based Analysis to Inform User-Centred Human-Building Interactions

OIA is a stepping stone in a larger research program to generate new metrics for evaluating designs. Such metrics can be used to measure current performance and evaluate the effectiveness of a given design. In office environments, a common but poorly studied goal of design is to measure “productivity” of people within the space. Human behavior is both complex and difficult to measure objectively. With Project SOIA, we aim to ultimately investigate how the layout of furniture within an office environment influences a factor in productivity, the social behavior within that space. For example, in project Discover, work style preferences were gathered through surveys to understand people’s preferences with respect to light, ‘buzz’, views to the outside and other supporting elements that can influence comfort and productivity. These preferences were encoded and measured against during generative design. With SOIA, we are studying the structure, features and frequencies of social interactions to generate a preliminary understanding of how we can generate new, possibly automated, evaluative metrics for furniture layout and room typology within a given design. Beyond this contribution, we are also aiming to investigate the effectiveness and social acceptance of using modern Computer Vision techniques to analyze human behavior while respecting privacy. SOIA will generate a dataset for the training of recognition algorithms to further CV and could leads towards new insights into the automation of the evaluation of interior layouts and their effectiveness in supporting various desired workstyles and preferences.

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Socio-Spatial Comfort: Using Vision-based Analysis to Inform User-Centred Human-Building Interactions

Bokyung Lee, Michael Lee, Pan Zhang, Alexander Tessier, Daniel Saakes, Azam Khan

Conference on Computer-Supported Cooperative Work and Social Computing 2020 (Best Paper Award)

A well-designed workplace has a direct and significant impact on our work experiences and productivity. In this paper, we investigate how office interior layouts influence the way we socially experience office buildings. We extend the previous work that examined static social formations of office workers by looking at their dynamic movements during informal desk visiting interactions. With a month of video data collected in the office, we implemented a vision-based analysis system that enables us to examine how people occupy space in social contexts in relation to desk configurations. The results showed that both social territoriality and approach path highlight social comfort in human-building interactions, which are different from efficiency or path optimization. From these findings, we propose the concepts of socio-spatial comfort: social buffers, privacy buffers, and varying proxemics to inform a user-centered way of designing human building interactions and architecture

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