The deployment of power line communication technology for broadband video streaming remains a challenge because power lines are not originally designed for signal transmission. Scalable video is a viable approach that can cope with the bandwidth fluctuation of power line communication networks provided that the bandwidth information is available. In this paper we first investigate how the interference caused by electrical appliances or power supplies affects the power line channel bandwidth and packet transmission. Then we take the obtained characteristics of in-home power line network into account in the design of a simple but effective heuristic-based application-layer bandwidth estimation scheme, for which the cutoff rate is estimated from the packet size and the physical-layer data rates. Experimental results show that the proposed approach can effectively combat the noise interference and deliver robust video streaming over power line.

Client-side data buffering is a common technique to deal with media playout interruptions of streaming video caused by network jitters and packet losses of best-effort networks. However, stronger playout interruption protection inevitably amounts to larger data buffering and results in more memory requirements and longer playout delay. Adaptive media playout (AMP), also a client-side technique, can reduce the buffer requirement and avoid buffer outage but at the expense of visual quality degradation because of the fluctuation of playout speed. In this paper, we propose a novel AMP scheme to keep the video playout as smooth as possible while adapting to the channel condition. The triggering of the playout control is based on buffer variation rather than buffer fullness. Experimental results show that our AMP scheme surpasses conventional schemes in unfriendly network conditions. Unlike previous schemes that are tuned for a specific range of packet loss and network instability, the proposed AMP scheme maintains consistent performance across a wide range of network conditions.

HotStreaming is an overlay peer-to-peer (P2P) based IPTV system. It integrates the innovations in both overlay networking and video coding for optimal user experience. The HotStreaming system is composed of three key components: partnership formation, data request scheduling and multiple description coding (MDC). In the partnership formation component, we propose two policies to reduce the time of disconnection and the number of isolated peers. In the MDC component, we adopt MDC with spatial-temporal hybrid interpolation (MDC-STHI), which makes the peers in a P2P network to adjust the streaming traffic according to their bandwidth limitation and capability of devices. The experimental results show that the HotStreaming system improves the video quality over a lossy and dynamic networking environment.

NTUStreaming is an overlay P2P-based IPTV system that integrates innovations in both overlay networking and video coding for optimal user experience. The system consists of three key components: partnership formation, robust video coding, and video segment request scheduling. For partnership formation, a graph construction mechanism TYPHOON based on epidemic algorithms is developed to reduce disconnect time and isolated peers. For robust video coding, a multiple description coding (MDC) scheme with spatial-temporal hybrid interpolation (STHI) is proposed to adjust streaming traffic according to the bandwidth and device capability of each peer. For request scheduling, an optimization algorithm is developed by taking the available bandwidth and the video segment type into account. Experimental results show that NTUStreaming is able to deliver optimal video quality in lossy and dynamic networking environments.

The quality of media streaming over best-effort networks suffers from network delays and packet losses. The latter is more profound for wireless video. To enhance the QoS of streaming services, adaptive media playout (AMP) has been developed to adjust the playout interval. With AMP, the risk of delay and buffer underflow is reduced. However, the smoothness of playback is not guaranteed. In this paper, we propose a novel AMP control that enables smooth playout and meanwhile maintains reliable visual quality. Our AMP control adjusts the playout interval based on an estimation of channel quality, so it is more adaptive than conventional AMP controls that are based on buffer fullness. Experimental results are provided to justify our approach. Even at 20% packet loss rate, the proposed AMP control is still able to provide smooth and reliable playback

The number of client requests that a streaming server can handle is limited by both its computational resources and available bandwidth. While bandwidth capacity is critical for most streaming applications, computational resources for a server encoding live videos often become a critical factor as well. In order to serve more client requests or provide higher quality for high priority clients, it is desirable to allocate and adjust the computational resources on a per channel basis. In this paper, we proposed a complexity-aware live video streaming server system that manages the computational resources dynamically. In the proposed system, input videos are encoded with different quality levels based on their priorities and available computational resources. The computational resources for each encoder are adaptively allocated to match the time constraints. The seven quality levels defined in the XviD MPEG-4 encoder are used in our experiments. The results show that the new design is able to maximize the resource utilization by maintaining the highest priority channels quality while providing the other channels with best-effort quality.

A digital image stabilization system compensates the image movement caused by hand jiggle for the image sequence captured by a hand-held video camera. In this paper, a simplified stabilization algorithm based on our previous work is presented. The algorithm performs block-based motion estimation on 16 local 16/spl times/16 blocks and uses a median filter to estimate the global motion. It reduces the complexity by confining the motion estimation to a small number of blocks of the image. This greatly facilitates the implementation of the algorithm on BF561, a DSP processor of analog device. Details of the DSP implementation are described.

For a live streaming server, it is highly desirable to allocate the available computational resource and bandwidth to each channel fairly and efficiently. In this paper, we propose a complexity-aware live streaming system with bit rate adjustment that can handle the allocation of bandwidth and computational resource of a live streaming server. The proposed system encodes the input videos at different quality levels based on the priority of the input videos and the available computational resource. It incorporates a bit rate adjustment mechanism to compensate for the video quality drop resulted from the quality level change of high priority encoders. The resulting system is able to handle channels more efficiently because the complexity of high priority encoders can also be dynamically adjusted with little quality drop. A new complexity adjustment method is developed that enables the system to stabilize more quickly and minimizes the variance of the time buffer. The experimental results show that the system can handle more channels while still maintaining the quality of high priority encoders. The proposed system is applicable to multimedia home gateways, surveillance, IP-based TV, and on-line sports game relays.