Intelligent video surveillance is an important topic in the field of computer vision and pattern recognition. Significant progress has achieved in the last decades, from object detection, tracking and parsing to activity recognition and video understanding. With the development of internet technology and the ubiquitous presence of low-cost surveillance cameras nowadays, surveillance video has become a typical big data, offering both opportunities and challenges for intelligent video surveillance. On one hand, the mass data involve more abundant information to mine. On the other hand, it suffers from various difficulties such as noise, label deficiency and computational complexity. This special session focuses on learning methods to achieve high performance video analysis and understanding under uncontrolled environments in large scale, which is also a very challenging problem. Moreover, it attracts much attention from both the academia and the industry. We hope this topic will aggregate top level works on the new advances in video analysis and understanding from big surveillance data. We will solicit original contributions of researchers and practitioners from the academia as well as industry, which address a wide range of theoretical and applied issues.
The topics of interest include, but are not limited to:
Paper submission deadline is on January 15, 2016