Delivering relevant video segments (video highlights) to a variety of devices operating under both wired and wireless platforms requires: (a) a mechanism for describing video content, and the environment in which it is to be delivered, and (b) a framework to support physical and semantic adaptation of a video. The aim of the adaptation process is to maximize users' viewing experiences of video quality and minimize resources required to deliver the content. Towards this, we have developed a quality driven adaptation algorithm and implemented a prototype system called DAVE. DAVE minimizes resource requirements by identifying relevant segments within a video and then scales the identified video segment in different dimensions so that it can be delivered within the available network bandwidth, and played back by the client device. Simultaneously, it maximizes the video quality by identifying and tuning relationships between perceptual quality parameters such as frame rate and frame size, with network and device resources such as bit rate, to maximize user-viewing experience. In this paper, we present a quality-driven adaptation algorithm and its implementation through the DAVE system.
['Surya Nepal', 'Uma Srinivasan']
DAVE: a system for quality driven adaptive video delivery