Abstract
BackgroundMixed reality (MR) video fusion systems merge video imagery with 3D scenes to make the scene more realistic and help users understand the video content and temporal–spatial correlation between them, reducing the user′s cognitive load. MR video fusion are used in various applications; however, video fusion systems require powerful client machines because video streaming delivery, stitching, and rendering are computationally intensive. Moreover, huge bandwidth usage is another critical factor that affects the scalability of video-fusion systems. MethodsOur framework proposes a fusion method for dynamically projecting video images into 3D models as textures. ResultsSeveral experiments on different metrics demonstrate the effectiveness of the proposed framework. ConclusionsThe framework proposed in this study can overcome client limitations by utilizing remote rendering. Furthermore, the framework we built is based on browsers. Therefore, the user can test the MR video fusion system with a laptop or tablet without installing any additional plug-ins or application programs.
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