Interaction designers' perceptions of using motion-based full-body features. Issue 155 (November 2021) - Escamilla, Antonio; Melenchón, Javier; Monzo, Carlos; Morán, Jose Antonio
Highlights: We investigated the perceptions of using feature extraction technologies in interaction designers. We evidence practitioners' approaches towards computer vision technology. We look at how professional backgrounds shape perceptions about the role of technology. Interaction designers consider motion-based feature extraction to be challenging and time-consuming. Designer interpretable features as a potential tool to foster user behavior exploration. Abstract: Movement-based full-body interactions are increasingly being used in the design of interactive spaces, computer-mediated environments, and virtual user experiences due to the development and availability of diverse sensing technologies. In this context, the role of interaction designers is to find systematic and predictable relationships between bodily actions and the corresponding responses from technology. Sensor-based interaction design relies on sensor data analysis and higher-level feature extraction to improve detection capabilities. However, understanding human movement to inform the design of motion-based interactions is not straightforward if the detection capabilities of interaction technologies are unknown. We aim at understanding the problems and opportunities that practitioners—regardless of their technical background—perceive in using different motion-based full-body features. To achieve this, we conducted four separate focus groups with experienced practitioners, with and without technical backgrounds. We used a framework for the analysis of focus group data in information systems research to identify content areas and draw conclusions. Our findings suggest that most interaction designers, regardless of their technical background, consider motion-based feature extraction to be challenging and time-consuming. However, participants acknowledge they might use designer-interpretable features as a potential tool to foster user behavior exploration. Understanding how practitioners link sensor-based interaction design with feature extraction technology is relevant to design computational tools and reduce the technical effort required from designers to characterize the user's movement.