Hung T. Le

An Evaluation of Bitrate Adaptation Methods for HTTP Live Streaming

HTTP streaming has become a cost-effective means for multimedia delivery nowadays. For adaptivity to networks and terminals, a provider should generate multiple representations of an original video as well as the related metadata. Recently, there have been various adaptation methods to support adaptive HTTP streaming. In this paper, we investigate typical adaptation methods in the context of live video streaming. We first discuss the trade-off among typical adaptation methods. The evaluation and comparison are then carried out not only in terms of bitrate and buffer behaviors but also in terms of the perceptual impact on end users. It is found that the perceptual impact depends not only on adaptation method but also on the content itself. We also show that the preparation of representation sets may affect the behaviors of some adaptation methods.

Adaptive video streaming over HTTP with dynamic resource estimation

Adaptive hypertext transfer protocol (HTTP) streaming has become a new trend to support adaptivity in video delivery. An HTTP streaming client needs to estimate exactly resource availability and resource demand. In this paper, we focus on the most important resource which is bandwidth. A new and general formulation for throughput estimation is presented taking into account previous values of instant throughput and round trip time. Besides, we introduce for the first time the use of bitrate estimation in HTTP streaming. The experiments show that our approach can effectively cope with drastic changes in connection throughput and video bitrate.

Buffer-based bitrate adaptation for adaptive HTTP streaming

Live and on-demand video streaming has recently contributed a significant part of the Internet traffic. In order to guarantee the best possible user experience, multimedia service is required to support large fluctuations in different network conditions. One of the cost effective means for multimedia delivery nowadays is HTTP streaming. The key challenge of this technology is how to change adaptively video bitrates according to network variation and client buffer while bestowing upon users the best possible video quality. In this paper, we propose a novel rate-adaptation method on client side, which allows clients to estimate buffer level in the future, and thus achieving a balance between the need for high video quality and buffer stability. The experiments show that our method performs well under varying network conditions.

Quality-driven bitrate adaptation method for HTTP live-streaming

In this paper, we focus on the bitrate adaptation issue of HTTP live video streaming. We first present a systematic approach that enables the client to choose the best video quality when deciding video bitrate for next several segments. After that, based on the concept of JND (Just Noticeable Difference), an adaptation method is proposed to meet the tradeoff between the requirements of buffer stability and smooth video quality. The experiment results show that our proposed method can provide smooth videos in terms of perceptual quality even under a small buffer size (i.e. 10s). To the best of our knowledge, this paper presents for the first time the way to use a perceptual quality metric for adaptivity in HTTP streaming.

A Novel Adaptation Method for HTTP Streaming of VBR Videos over Mobile Networks

Recently, HTTP streaming has become very popular for delivering videos over the Internet. For adaptivity, a provider should generate multiple versions of a video as well as the related metadata. Various adaptation methods have been proposed to support a streaming client in coping with strong bandwidth variations. However, most of existing methods target at constant bitrate (CBR) videos only. In this paper, we present a new method for quality adaptation in on-demand streaming of variable bitrate (VBR) videos. To cope with strong variations of VBR bitrate, we use a local average bitrate as the representative bitrate of a version. A buffer-based algorithm is then proposed to conservatively adapt video quality. Through experiments in the mobile streaming context, we show that our method can provide quality stability as well as buffer stability even under very strong variations of bandwidth and video bitrates.

Request adaptation for adaptive streaming over HTTP/2

In this paper, we propose a client-based adaptation method for Adaptive Streaming over HTTP/2 leveraging the server push feature. A cost function that takes into account both the number of pushed segments and the playout buffer level is defined. Experiment results show that the proposed method can improve the tradeoff between the number of requests and buffer stability compared to existing solutions.

Smooth-bitrate adaptation method for HTTP streaming in vehicular environments

Recent years have seen a fast growth of video on-demand (VOD) services over HTTP. In order to improve service quality, video services are required to support different network conditions. For vehicular environments, this study proposes a novel adaptation method that improves quality of experience (QoE) by 1) reducing the number of bitrate switches and 2) avoiding sudden quality changes. The experiment shows that proposed method can provide a smooth video even under highly fluctuating network conditions.

Adaptive mobile streaming over HTTP/2 with gradual quality transitions

In this paper, we study an adaptation method for mobile streaming over HTTP/2. Beside leveraging the server push feature of HTTP/2 to reduce request-related overheads, the proposed method can improve video quality by delivering gradual video bitrate transitions. Experimental results show that our method can provide smooth video quality while resulting in a low number of requests over a whole session.

Future buffer based adaptation for VBR video streaming over HTTP

HTTP streaming has become a cost effective means for video delivery nowadays. To enable adaptivity to networks and terminals, a provider should generate multiple representations of an original video as well as the related signaling metadata. So far, most previous studies have just focused on the case of CBR (constant bit rate) video. In this paper, we propose a novel adaptation method for VBR (variable bitrate) video streaming. Based on a trellis representation to estimate future buffer levels, the proposed method can provide smooth video quality while avoiding buffer underflows. The experimental results show that our approach can perform effectively under drastic changes of both connection throughput and video bitrate.

Design and implementation of an e-Health system for depression detection

We present the design and implementation of a cost-effective e-Health system for automatic depression detection. The system is based on a client-server architecture, where clients are popular mobile devices. For practical deployment, various factors that affect the accuracy and speed of depression detection are discussed and evaluated with extensive experiments.