Video surveillance technologies are widely used in urban security systems today. Intelligent video analytics are an important aspect of video surveillance technology, using image recognition processing to identify the existence of security threats that have already occurred or may occur in the future, and alerting users in real-time.
Video surveillance technologies are widely used in urban security systems today. Intelligent video analytics are an important aspect of video surveillance technology, using image recognition processing to identify the existence of security threats that have already occurred or may occur in the future, and alerting users in real-time.
Video analytics used in common surveillance systems include the following functionalities:
(1) Transfer video from IP camera or local files, and decode the input video stream into original image data in YUV format.
(2) Render decoded video into the format required by the video analytics algorithm. This often requires color format changing, down-scaling, noise reduction and color space conversion to the YUV data.
(3) Execute video analytics algorithm against the rendered video picture sequence. Interesting objects or events (recognized object moving in a pattern) are identified. They are highlighted on the monitor display and also indexed for fast future retrieval.
(4) Trigger audio alarm or SMS to alert the user to take action if the pre-defined thresholds/rules are reached.
The increasing need for real-time video analytics presents a big challenge to video surveillance providers today. Real-time video analytics requires that videos be collated and processed immediately, providing meaningful, actionable data that can be used in real-time. In addition, successfully harnessing big-data processing technology to quickly identify required video segments becomes more difficult with the increasing volume of video data used in analytics. ( read more...)
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