Rich media application enables plenty of interactive, information-rich services to enhance end user's viewing experience. In current standards released for such service, only one rendering space is defined to handle multiple types of content belonging to the same service. However, a new trend is to assign more than one terminal device to render rich media application in a cooperative way inside a digital connected home network. The conventional audio-visual synchronization mechanism is focused on the packet level QoS (quality of service) control with less consideration of viewing experience. However, the actual QoE (quality of experience) is the final viewer's subjective perception for the displaying visual element. In order to design an optimized media distribution system based on QoE, this paper firstly introduces a subjective visual synchronization test for the same or tight relating contents rendering in dual screens, where the relationship between delay variation and the end user's evaluation is explored. Secondly, a QoE based media distribution mechanism is proposed to dynamically adjust the media flow transmission rate by using delay variation reports from terminals; at the same time, the tradeoff between rate adaptation and buffer overload is also considered. Simulation results show the proposed algorithm can not only improve the overall QoE score under either discrete or continuous delay variations; but also outperform the delay guarantee solutions without consideration of QoE.

Ubiquitous computing technology has brought great attentions in recent years since it promises a simple operation to an ever increasing comprehensive digital world. For a networked home supporting advanced applications, ubiquitous media access becomes a must to offer enjoyable experience for home users. The first step of ubiquitous computing is the seamless detection of user activities in order to offer services correspondingly. The challenge of user activity detection in a home is multi folds, which includes constraints on cost, privacy, energy and health concerns. This paper proposes an indoor location detection solution based on a multi modal sensor network with radio signal and cameras. With an adaptive learning estimation algorithm for noise and radio signal, by processing the combination of radio signal and image from camera, radio signal detection thresholds which controls the camera power on and cut off are generated and updated, reflecting the dynamic environment change. In this processing, no manual explicit training is needed. Simulation results show our method is very effective in terms of the determination of when to power on/off the camera.