Name
Abstract | ||
|---|---|---|
The paper presents a perceptual optimized adaptive HTTP streaming scheme to improve the quality of experience (QoE). In addition to barely controlling the bandwidth and buffer size in existing works, this paper integrates the video saliency based adaptation to improve the perceptual quality for end users. Resources (e.g., buffer) are well managed using saliency cues to ensure the smooth quality under a given network bandwidth. Algorithms are implemented on top of the open-source DASH platform - dash.js to demonstrate our superiority compared with the default throughput-based adaptation and well-known BOLA method. Our work can be a potential enhancement for current DASH standard to offer the smooth and perceptual optimized adaptive streaming in mobile networks. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/VCIP.2017.8305118 | 2017 IEEE Visual Communications and Image Processing (VCIP) |
Keywords | Field | DocType |
HTTP adaptive streaming,video rate adaptation,MPEG-DASH,video perceptual model,QoE optimization,wireless communication | Computer vision,Computer architecture,Wireless,End user,Salience (neuroscience),Computer science,Bandwidth (signal processing),Quality of experience,Artificial intelligence,Throughput,Perception,Dash | Conference |
ISBN | Citations | PageRank |
978-1-5386-0463-2 | 0 | 0.34 |
References | Authors | |
6 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Huaying Xue | 1 | 0 | 0.68 |
| Yuan Zhang | 2 | 121 | 46.72 |
| Jinyao Yan | 3 | 5 | 3.86 |