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- W3149262241 abstract "We present a system, predicting the point in time when users of a public display are about to leave. The ability to react to users' intention to leave is valuable for researchers and practitioners alike: users can be presented additional content with the goal to maximize interaction times; they can be offered a discount coupon for redemption in a nearby store hence enabling new business models; or feedback can be collected from users right after they have finished interaction without interrupting their task. Our research consists of multiple steps: (1) We identified features that hint at users' intention to leave from observations and video logs. (2) We implemented a system capable of detecting such features from Microsoft Kinect's skeleton data and subsequently make a prediction. (3) We trained and deployed a prediction system with a Quiz game which reacts when users are about to leave (N=249), achieving an accuracy of 78%. The majority of users indeed reacted to the presented intervention." @default.
- W3149262241 created "2021-04-13" @default.
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- W3149262241 date "2021-03-19" @default.
- W3149262241 modified "2023-10-13" @default.
- W3149262241 title "Orbuculum - Predicting When Users Intend to Leave Large Public Displays" @default.
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- W3149262241 doi "https://doi.org/10.1145/3448075" @default.
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