<P><B>Abstract</B></P> <P>In this paper, we propose an estimation method that estimates the throughput of upcoming video segments based on variations in the network throughput observed during the download of previous vid...
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https://www.riss.kr/link?id=A107508655
2017
-
SCOPUS,SCIE
학술저널
433-446(14쪽)
0
상세조회0
다운로드다국어 초록 (Multilingual Abstract)
<P><B>Abstract</B></P> <P>In this paper, we propose an estimation method that estimates the throughput of upcoming video segments based on variations in the network throughput observed during the download of previous vid...
<P><B>Abstract</B></P> <P>In this paper, we propose an estimation method that estimates the throughput of upcoming video segments based on variations in the network throughput observed during the download of previous video segments. Then, we propose a rate-adaptive algorithm for Hypertext Transfer Protocol (HTTP) streaming. The proposed algorithm selects the quality of the video based on the estimated throughput and playback buffer occupancy. The proposed method selects high-quality video segments, while minimizing video quality changes and the risk of playback interruption, improving user’s experience. We evaluate the algorithm for single- and multi-user environments and demonstrate that it performs remarkably well under varying network conditions. Furthermore, we determine that it efficiently utilizes network resources to achieve a high video rate; competing HTTP clients achieve equitable video rates. We also confirm that variations in the playback buffer size and segment duration do not affect the performance of the proposed algorithm.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Throughput estimation method based on the throughput observed over past segments. </LI> <LI> Rate adaptive algorithm based on the buffer occupancy and estimated throughput. </LI> <LI> Selects high-quality video segments, while minimizing video quality changes. </LI> <LI> Minimizes the risk of playback interruption. </LI> <LI> Competing HTTP clients achieve equitable video rates. </LI> </UL> </P>
Saliency detection for panoramic landscape images of outdoor scenes