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- W2785902205 abstract "This paper presents a perceptual optimization scheme for the adaptive HTTP streaming services. It is well-known that the content features have deep influence on the user’s quality of experience (QoE). However, most of the existing algorithms only consider bandwidth and buffer in quality control. This paper integrates the video-saliency-based adaptation to improve the perceptual quality for end users. The saliency cues, the network condition and the buffer status are jointly considered to manage the resources (e.g., buffer) efficiently. In particular, both the saliency cues of current segment and segments from adjacent shots are taken into consideration. The heuristic adaptation 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 has high potential to enhance the current DASH standard by offering the smooth and perceptually optimized adaptive streaming in mobile networks." @default.
- W2785902205 created "2018-02-23" @default.
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- W2785902205 date "2018-01-01" @default.
- W2785902205 modified "2023-09-26" @default.
- W2785902205 title "A Perceptual Optimization Approach to Adaptive HTTP Streaming" @default.
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- W2785902205 doi "https://doi.org/10.1007/978-981-10-8108-8_35" @default.
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