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Framework Design for Multiplayer Motion Sensing Game in Mixture Reality

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MultiMedia Modeling (MMM 2020)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11962))

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Abstract

Mixed reality (MR) is getting popular, but its application in entertainment is still limited due to the lack of intuitive and various interactions between the user and other players. In this demonstration, we propose an MR multiplayer game framework, which allows the player to interact directly with other players through intuitive body postures/actions. Moreover, a body depth approximation method is designed to decrease the complexity of virtual content rendering without affecting the immersive fidelity while playing the game. Our framework uses deep learning models to achieve motion sensing, and a multiplayer MR interaction game containing a variety of actions is designed to validate the feasibility of the proposed framework.

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Notes

  1. 1.

    Microsoft Hololens, https://www.microsoft.com/en-us/hololens.

  2. 2.

    Magic Leap, https://www.magicleap.com/magic-leap-one.

  3. 3.

    Windows Mixed Reality, https://www.acer.com/ac/zh/TW/content/series/wmr.

  4. 4.

    Pool Nation VR, https://www.roadtovr.com/pool-nation-vr-review-htc-vive-steam/.

  5. 5.

    NIANTIC AR Games, https://nianticlabs.com/zh_hant/blog/nrwp-update/.

  6. 6.

    Fact or Fantasy? https://www.framestore.com/work/fact-or-fantasy.

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Acknowledgement

This research was supported by the Ministry of Science and Technology (Contract MOST 108-2218-E-007-055, 108-2221-E-007-106-MY3, and 108-2627-H-155-001), Taiwan.

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Correspondence to Min-Chun Hu .

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Chang, CY., Chuang, BI., Hsia, CC., Chen, WC., Hu, MC. (2020). Framework Design for Multiplayer Motion Sensing Game in Mixture Reality. In: Ro, Y., et al. MultiMedia Modeling. MMM 2020. Lecture Notes in Computer Science(), vol 11962. Springer, Cham. https://doi.org/10.1007/978-3-030-37734-2_57

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  • DOI: https://doi.org/10.1007/978-3-030-37734-2_57

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-37733-5

  • Online ISBN: 978-3-030-37734-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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