Auflistung nach Autor:in "Koelle, Marion"
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- WorkshopbeitragInteraction in the Public: Aesthetics, Social Acceptability, and Social Context(Mensch und Computer 2021 - Workshopband, 2021) Uhde, Alarith; Tretter, Stefan; von Terzi, Pia; Koelle, Marion; Diefenbach, Sarah; Hassenzahl, MarcEven in moments considered private, others often witness how we interact with technology. A typical example is smartphone use at home, in the presence of family members. This of course becomes even more likely in public - on streets, in libraries, or in the supermarket, places full of other people. The social context brings challenges and opportunities. When designing interaction, we often primarily focus on what users experience, like, and accept. Less do we explicitly consider what present others may think or feel about this interaction, and how it relates to their own current activities. This requires a deeper understanding of social context and frugal but sufficiently rich context descriptions. In turn, considering present others allows us to learn about what types of interaction are acceptable or even aesthetic in what types of context. In this workshop, we collaboratively explored the largely untouched questions of positive interaction from the perspective of others, and worked out ways in which these could improve the design process.
- WorkshopbeitragTowards Respectful Smart Glasses through Conversation Detection(Mensch und Computer 2018 - Tagungsband, 2018) Meirose, Franziska; Schultze, Sven; Kuehlewind, Sebastian; Koelle, Marion; Abdenebaoui, Larbi; Boll, SusanneTalking to each other is personal, maybe even intimate. Thus, privacy expectations are particularly high during interpersonal conversations, and image or audio recordings are problematic in these contexts. In consequence, smart glasses and other body-worn devices with “always-on” cameras are not well accepted during interpersonal conversations. Proposing a simple-to-implement computer vision procedure, we work towards a solution to this issue. Using imagery from a head-worn camera we detect face-to-face conversations in real-time, as well as distinguish between intimate, personal and social conversations based on intrinsic camera parameters. Starting from a fictive scenario, we illustrate how this knowledge can be used for interaction designs that increase both, the users’ as well as their bystanders’ privacy, e.g., by muting audio or disabling the camera. Finally, we suggest directions for future work.