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ThinkMind // MMEDIA 2020, The Twelfth International Conference on Advances in Multimedia // View article mmedia_2020_2_30_50029


Promoting Fluency of Streaming Video by Learning Human Perceptive Traits to Reveal the Vital Section in Outstanding Quality

Authors:
Shu Chiao Chiang
Tatsuo Nakajima

Keywords: Image processing; deep learning; accelerated streaming; media data structure

Abstract:
Currently, the quality of digital media and the quantity of contents are both increasing rapidly. For instance, watching e-sport competitions often suffers from unstable bandwidth, which causes the video to stutter or have a low resolution. In this situation, users will have a negative experience. Many situations can cause problems of congestion in real-time applications or 3D displays. To solve this kind of problem, we attempt to determine an inverse solution according to the path. This project adopts a reverse operation that reduces necessary data but maintains the same quality perception of user experience by utilizing the characteristics of the human vision and brain. To explore our approach, we develop a prototype that changes the resolution of the image according to a user’s habit and shows the part in focus clearly while leaving the resolution of the background lower. It selects interested sub-image in pictures and only displays them with higher quality to achieve a lower transmission requirement. This optimization will allow the user experience smoother streaming when there is congestion or unstable situations. Then, we conduct a preliminary user study to investigate some future directions and explore some potential flaws.

Pages: 30 to 34

Copyright: Copyright (c) IARIA, 2020

Publication date: February 23, 2020

Published in: conference

ISSN: 2308-4448

ISBN: 978-1-61208-772-6

Location: Lisbon, Portugal

Dates: from February 23, 2020 to February 27, 2020

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