With the rapid growth of IPTV and mobile video applications and driven by urgent demands from industry and users, the technologies of video processing and content sharing have received significant research attention in recent years. Video streaming in novel formats, such as ultra-high definition (UHD) and 3D, gives users an extra dimension of visual sense that greatly improves the liveliness and joyfulness of user experience. However, it also raises new challenges in video processing, coding, presentation and communication as well as in achieving satisfactory Quality of Experience (QoE) performance, especially when media devices (e.g., mobile clients) are resource (i.e., bandwidth, power, and computation) constrained. This calls for alternative solutions for sharing video contents effectively among end users. A media cloud computing system that performs multimedia processing and storage, and provides heterogeneous multimedia services is a natural solution to meet the call and also to remedy the lack of local resources in mobile clients. Cloud-based video processing and content sharing networks are promising technologies to orchestrate the video distribution between the mobile clients and the media cloud system. There is a strong need to develop advanced video processing, communication and network protocols, algorithms, and content sharing strategies for such a media cloud system. Many emerging and challenging issues have to be addressed, such as video collaboration and adaptation through the cloud, flexible media network resource management between cloud and mobile clients, and dynamic access and sharing through media cloud, and etc. The objective of this special issue is to identify and promote the necessary enabling media cloud based video processing and content sharing technologies for future anywhere and anytime video streaming applications.

Topics

The main purpose of this Special issue is to promote further research interests and activities related to cloud-based video processing and content sharing in view of its vast geographical span, multiple multimedia networking technologies, and multiple applications with heterogeneous requirements. To this end, we are soliciting analytical, experimental, and systems-related papers in all aspects of video processing and content sharing for media cloud. The topics of interest include, but are not limited to, the following:

• Video processing and communications for media cloud
• Cloud-based video content sharing network
• Network coding for UHD and 3D video content dissemination via cloud
• Resource balance between media cloud and mobile clients
• Multimedia social networks for video distribution over cloud
• Cloud based video presentation for mobile clients
• Media cloud resource management
• Cloud-assisted media content recommendation
• User-centric media adaptation in the cloud
• Video content sharing via media cloud
• Mobility management for cloud based video content sharing
• Media cloud and future Internet (e.g., SDN, NDN)
• Cloud-based video system and applications
• Optimization (e.g., energy, monetary cost) for media cloud
• Video editing/authoring on mobile devices with cloud support
• Security and privacy
• Social networks and media cloud
• Cloud-enabled media content search system
• Cloud-based mobile audio/video streaming techniques

Paper Submission
Only original and unpublished research papers will be considered in this special issue. All submissions will be reviewed based on technical merit and relevance. Authors should follow the IEEE Transaction on Multimedia manuscript format described in the Information for Authors at http://www.signalprocessingsociety.org/tmm/. Guidelines for prospective authors can be found on-line at http://www.signalprocessingsociety.org/tmm/tmm-author-info/ ). Prospective authors should submit an electronic copy of their complete manuscript in pdf format to the IEEE Transactions on Multimedia online manuscript system via http://mc.manuscriptcentral.com/tmm-ieee according to the following timetable:

Guest Editors:

Honggang Wang, University of Massachusetts Dartmouth, hwang1@umassd.edu
Sanjeev Mehrotra, Microsoft Research, sanjeevm@microsoft.com
Maria Martini, Kingston University, m.martini@kingston.ac.uk
Dapeng Wu, University of Florida, wu@ece.ufl.edu
Qian Zhang, Hong Kong University of Science and Technology, qianzh@cse.ust.hk