Improved DASH for Cross-Random-Access Prediction Structure in Video Coding
Hualong Yu, Lu Yu · 2018
In video coding, temporal correlations between pictures are utilized by short-term and long-term reference, which are limited inside a random access segment and cannot cross random access points (RAPs). To improve coding efficiency, correlations across RAPs are exploited by some novel video coding schemes. The cross-random-access prediction structure results in alterable dependency between pictures, which is affected by random access and different from the fixed dependency in conventional video coding standard. However, current media streaming scheme, such as Dynamic Adaptive Streaming over HTTP (DASH), cannot describe dependency across RAPs. This paper introduces the cross-random-access dependency description in DASH syntax. With dependency information, client can download segments in proper temporal order but may re-download segments. This paper further improves downloading management in client. Experiments show that improved DASH system transmitting stream with cross-random-access prediction structure can save 22.1% on maximum and 14.3% on average transmission bits in contrast to conventional DASH system.