Abstract
Dogsperate Escape is a visually attractive exercise game that allows the player to perform various activities, provoking physical exercises with a memorable experience. This paper presents an implementation of the motion control module in the game based on a bio-inspired, accelerometer embedded e-AR sensor. The acceleration signals from the device are wirelessly transmitted to the PC for real-time activity analysis. A real-time activity recognition algorithm has been constructed based on pre-collected datasets acquired from ten subjects while performing a simple pre-defined activity routine. The algorithm is validated on eleven different subjects while performing another activity routine. By integrating the algorithm into the game, the recognized activities can be mapped into specific input commands for character control.
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Zintus-art, K., Saetia, S., Pongparnich, V., Thiemjarus, S. (2011). Dogsperate Escape: A Demonstration of Real-Time BSN-Based Game Control with e-AR Sensor. In: Theeramunkong, T., Kunifuji, S., Sornlertlamvanich, V., Nattee, C. (eds) Knowledge, Information, and Creativity Support Systems. Lecture Notes in Computer Science(), vol 6746. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24788-0_23
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DOI: https://doi.org/10.1007/978-3-642-24788-0_23
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