Hapticseer: A multi-channel, black-box, platform-agnostic approach to detecting video game events for real-time haptic feedback

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Abstract

Haptic feedback signifcantly enhances virtual experiences. However, supporting haptics currently requires modifying the codebase, making it impractical to add haptics to popular, high-quality experiences such as best selling games, which are typically closed-source. We present HapticSeer, a multi-channel, black-box, platform-agnostic approach to detecting game events for real-time haptic feedback. The approach is based on two key insights: 1) all games have 3 types of data streams: video, audio, and controller I/O, that can be analyzed in real-time to detect game events, and 2) a small number of user interface design patterns are reused across most games, so that event detectors can be reused efectively. We developed an open-source HapticSeer framework and implemented several real-time event detectors for commercial PC and VR games. We validated system correctness and real-time performance, and discuss feedback from several haptics developers that used the HapticSeer framework to integrate research and commercial haptic devices.

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APA

Lin, Y. H., Wang, Y. W., Ku, P. S., Cheng, Y. T., Hsu, Y. C., Tsai, C. Y., & Chen, M. Y. (2021). Hapticseer: A multi-channel, black-box, platform-agnostic approach to detecting video game events for real-time haptic feedback. In Conference on Human Factors in Computing Systems - Proceedings. Association for Computing Machinery. https://doi.org/10.1145/3411764.3445254

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