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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. 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. The submitted manuscripts were reviewed by experts from both academia and industry. After two rounds of reviewing, the highest quality manuscripts were accepted for this special issue. Totally, we have received 27 manuscripts and 14 papers are accepted. The accepted rate is about 50 %. This special issue will be published by Multimedia Tools and Applications as special issues. The paper by H. Wang et al. [8] proposed a novel color-based road detection method based on a boundary ratio prior, with which we are able to infer the confidence of a certain image region belonging to the road class. The paper by J. Yu et al. [11] illustrates the 3D facial animation by combining the parameterized model and muscular model. 3D hair was Multimed Tools Appl DOI 10.1007/s11042-016-3804-5

Guest Editorial: Multimedia Data Sensing and Analyzing of Surveillance Systems