Big data is an emerging paradigm applied to datasets whose size is beyond the ability of commonly used software tools to capture, manage, and process the data within a tolerable elapsed time. With the pervasive of the definition of the smart city, the surveillance system, huge number of video surveillance devices such as surveillance cameras (some statistics suggest that the number of public security surveillance cameras is 200 thousand in Shanghai ). The data volume of all video surveillance devices in Shanghai is up to 1 PB every day.
Understanding the semantics of surveillance device has been an important component in many video based applications. Manual annotation and tagging has been considered as a reliable source of video semantics. Unfortunately, manual annotation is time-consuming and expensive when dealing with huge scale of video data. However, the semantic gap between semantics and video visual appearance is still a challenge towards automated ontology-driven video annotation. Thus automatically understanding raw videos solely based on their visual appearance becomes an important yet challenging problem. Thus, it is important to accurately describe the video content and enable the organizing and searching potential videos.
This special issue wants to demonstrate the emerging issues in the realm of big data and models towards surveillance systems. Original and research articles are solicited in all aspects including theoretical studies, practical applications, and experimental prototypes. All submitted papers will be peer-reviewed and selected on the basis of both their quality and their relevance to the theme of this special issue. Potential topics include, but are not limited to:
• Surveillance systems novel theory, algorithm and applications
• Surveillance Data mining and analytics
• Surveillance Data semantics, scientific discovery and intelligence
• Surveillance Data placement, scheduling, and optimization
• Performance characterization, evaluation and optimization
• Volume, Velocity, Variety, Value and Veracity of Surveillance Data
• Storage and computation management of Surveillance Data
• Large-scale Surveillance data
• Sensor network, social network, mobile network and big data
• Surveillance data applications


Authors are encouraged to submit high quality, original work that has neither appeared in, nor is under consideration by, other journals. Manuscripts based on previously published conference papers must be extended substantially. All manuscripts will undergo the same rigorous Multimedia Tools and Applications review process. Manuscripts should be submitted to: http://mtap.editorialmanager.com/. Please choose “Multimedia Data sensing and analyzing from surveillance systems in the big data era” as the Article Type.

Important Dates
Paper submission: June 1, 2015
Review results to authors: August 1, 2015
Revised paper submission: September 1, 2015
Final acceptance notification: October 1, 2015

Guest Editors

Zheng Xu, Tsinghua University, China

Yunhuai Liu, The third research institute of the ministry public security, China