Super-Resolution Based Bitrate Adaptation for HTTP Adaptive Streaming for Mobile Devices

Nguyen M., Çetinkaya E., Hellwagner H., Timmerer C.

1st ACM Mile-High Video Conference, MHV 2022, Colorado, United States Of America, 1 - 03 March 2022, pp.70-76, (Full Text) identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1145/3510450.3517322
  • City: Colorado
  • Country: United States Of America
  • Page Numbers: pp.70-76
  • Keywords: ABR, HTTP adaptive streaming, Neural networks, Super-resolution
  • Yıldız Technical University Affiliated: No

Abstract

The advancement of hardware capabilities in recent years made it possible to apply deep neural network (DNN) based approaches on mobile devices. This paper introduces a lightweight super-resolution (SR) network, namely SR-ABR Net, deployed at mobile devices to upgrade low-resolution/low-quality videos and a novel adaptive bitrate (ABR) algorithm, namely WISH-SR, that leverages SR networks at the client to improve the video quality depending on the client's context. WISH-SR takes into account mobile device properties, video characteristics, and user preferences. Experimental results show that the proposed SR-ABR Net can improve the video quality compared to traditional SR approaches while running in real time. Moreover, the proposed WISH-SR can significantly boost the visual quality of the delivered content while reducing both bandwidth consumption and number of stalling events.