Bandwidth Adaptation for 3D Mesh Preview Streaming

Abstract : Online galleries of 3D models typically provide two ways to preview a model before the model is downloaded and viewed by the user: (i) by showing a set of thumbnail images of the 3D model taken from representative views (or keyviews); (ii) by showing a video of the 3D model as viewed from a moving virtual camera along a path determined by the content provider. We propose a third approach called preview streaming for mesh-based 3D objects: by streaming and showing parts of the mesh surfaces visible along the virtual camera path. This article focuses on the preview streaming architecture and framework and presents our investigation into how such a system would best handle network congestion effectively. We present three basic methods: (a) stop-and-wait, where the camera pauses until sufficient data is buffered; (b) reduce-speed, where the camera slows down in accordance to reduce network bandwidth; and (c) reduce-quality, where the camera continues to move at the same speed but fewer vertices are sent and displayed, leading to lower mesh quality. We further propose two advanced methods: (d) keyview-aware, which trades off mesh quality and camera speed appropriately depending on how close the current view is to the keyviews, and (e) adaptive-zoom, which improves visual quality by moving the virtual camera away from the original path. A user study reveals that our keyview-aware method is preferred over the basic methods. Moreover, the adaptive-zoom scheme compares favorably to the keyview-aware method, showing that path adaptation is a viable approach to handling bandwidth variation.
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ACM Transactions on Multimedia Computing, Communications and Applications, Association for Computing Machinery, 2014, vol. 10 (n° 1), pp. 1-20. 〈10.1145/2537854〉
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Shanghong Zhao, Wei Tsang Ooi, Axel Carlier, Géraldine Morin, Vincent Charvillat. Bandwidth Adaptation for 3D Mesh Preview Streaming. ACM Transactions on Multimedia Computing, Communications and Applications, Association for Computing Machinery, 2014, vol. 10 (n° 1), pp. 1-20. 〈10.1145/2537854〉. 〈hal-01120943〉

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