Content-Adaptive Spatial Scalability for Scalable Video Coding Applications
Today, TV and video services are consumed using various types of display devices, e.g. TV sets, tablets, or smart phones. We have a heterogeneous environment of display devices available, where different display aspect-ratios (e.g. 4:3, 16:9) and resolutions (e.g. SDTV, HDTV) are natively supported. Content is usually distributed using single resolution video coding like H.264/AVC which does not allow to control how video content is retargeted on the consumer side. SVC, the scalable extension of H.264/AVC, allows to jointly transmit several videos with different aspect-ratios and resolutions. If SVC is used, a video with the appropriate aspect-ratio could be decoded, while inherent dependencies between the transmitted videos are exploited for an efficient overall compression. However, SVC supports only retargeting by cropping and linear scaling. Recently, we developed a method for efficient Content-adaptive Video Retargeting, which is considered as one of the currently best performing video retargeting methods known in research. But this result leaves open the question of how to efficiently deliver retargeted video content to consumers with different aspect ratios?
In this project, a scalable video coder is developed, which can simultaneously compress several video streams that have different aspect ratios and have been created by content-adaptive retargeting, MPEG’s Scalable Video Coder is extended for this purpose. Both video streams image warps are encoded in a scalable way, where the warps are exploited for an efficient compression (i.e. exploitation of redundancies between video streams) by using different techniques for inter-layer prediction. With our extension, video content of higher semantic quality can be transmitted in a scalable way by introducing an average overhead in bit rate of 9.3%