The primal goal of this special issue is to organize excellent research results to track and identify objects, analyze motion, and extract video intelligence from analog or digital video streams automatically. At the same time, we focus on the efficiency of video surveillance systems and concentrate mainly on the machine learning methods which can be used to analyze video and control the machine automatically. Its aim is to unify the machine learning techniques as an integral concept that highlights the trends in advanced video intelligence and automated monitoring. We are soliciting papers that present recent results as well as more speculative presentations that discuss research challenges, define new applications, and propose methodologies for evaluating the roadmap for achieving the vision of intelligent video and automated monitoring.

The primal topic covers machine learning methods in intelligent video and automated monitoring. Potential topics include, but are not limited to:

• Objects recognition in image and video with machine learning
• Data mining in image and video automated analysis
• Optimization models in image and video compression and sensing
• Image and video automated acquisition with machine learning methods
• Image and video storage retrieval
• Applications of intelligent video and automated monitoring

Before submission authors should carefully read over the journal’s Author Guidelines, which are located at http://www.hindawi.com/journals/tswj/guidelines/. Prospective authors should submit an electronic copy of their complete manuscript through the journal Manuscript Tracking System at http://mts.hindawi.com/submit/journals/tswj/computer.science/autm/ according to the following timetable: