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Article

MonoMR: Synthesizing Pseudo-2.5D Mixed Reality Content from Monocular Videos

Department of Computer Science, School of Computing, Tokyo Institute of Technology, Tokyo 152-8550, Japan
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Author to whom correspondence should be addressed.
Academic Editor: Chang-Hun Kim
Appl. Sci. 2021, 11(17), 7946; https://doi.org/10.3390/app11177946
Received: 1 August 2021 / Revised: 24 August 2021 / Accepted: 25 August 2021 / Published: 27 August 2021
(This article belongs to the Special Issue Virtual and Augmented Reality Systems)
MonoMR is a system that synthesizes pseudo-2.5D content from monocular videos for mixed reality (MR) head-mounted displays (HMDs). Unlike conventional systems that require multiple cameras, the MonoMR system can be used by casual end-users to generate MR content from a single camera only. In order to synthesize the content, the system detects people in the video sequence via a deep neural network, and then the detected person’s pseudo-3D position is estimated by our proposed novel algorithm through a homography matrix. Finally, the person’s texture is extracted using a background subtraction algorithm and is placed on an estimated 3D position. The synthesized content can be played in MR HMD, and users can freely change their viewpoint and the content’s position. In order to evaluate the efficiency and interactive potential of MonoMR, we conducted performance evaluations and a user study with 12 participants. Moreover, we demonstrated the feasibility and usability of the MonoMR system to generate pseudo-2.5D content using three example application scenarios. View Full-Text
Keywords: augmented reality; computer vision; human-computer interaction augmented reality; computer vision; human-computer interaction
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MDPI and ACS Style

Hwang, D.-H.; Koike, H. MonoMR: Synthesizing Pseudo-2.5D Mixed Reality Content from Monocular Videos. Appl. Sci. 2021, 11, 7946. https://doi.org/10.3390/app11177946

AMA Style

Hwang D-H, Koike H. MonoMR: Synthesizing Pseudo-2.5D Mixed Reality Content from Monocular Videos. Applied Sciences. 2021; 11(17):7946. https://doi.org/10.3390/app11177946

Chicago/Turabian Style

Hwang, Dong-Hyun, and Hideki Koike. 2021. "MonoMR: Synthesizing Pseudo-2.5D Mixed Reality Content from Monocular Videos" Applied Sciences 11, no. 17: 7946. https://doi.org/10.3390/app11177946

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