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Video content analysis (also Video content analyticsVCA) is analyzing the video to detect and determine events not based on just a single image. As such, it can be seen as the automated process, unlike a human’s ability to see objects and activities and then ascribe meaning to them.

Examples of video content analysis techniques in different fields include Dynamic masking, Flame, and smoke detection, motion detection, shape recognition, object detection, video tracking, etc.

Video Content Analysis (VCA) is the capability of automatically analyzing video to detect and determine events not based on just a single image.

As such, it can be seen as the automated process, unlike human’s ability to see objects and activities and then ascribe meaning to them.

This technical capability is widely used in the security industry for better situation awareness.

The video data generated by IP CCTV cameras are used for data analysis to process, categorize and analyze the objects and activities captured.

The algorithms can be implemented as software on general purpose machines, or can be embedded in the IP CCTV camera’s video processing units.

Many capabilities can be implemented in VCA, some of them are as follows:

  • Motion detection: Video Motion Detection is one of the simpler forms of video analysis where motion is detected with regard to a fixed background scene. The region of interest can be set in the software for implementing analysis for a specific area.
  • People and or Object Counter: This is an ability to count the number of People and or Object pass through a defined region in the camera’s field of view.
  • Trip wire: The crossing of a boundary by any moving object within the camera’s view can be detected using this algorithm.
  • Heat Maps: It is an ability of the video analysis software algorithm to overlay heat maps on the video in a defined area of the camera’s view. The data analyzed by the software will provide information on a varying density of the object or people within the camera’s field of view in a given time interval.
  • Facial recognition is a computer application capable of identifying a person from a digital image or a video source. One of the ways to do this is by comparing selected facial features from the image and a face database, which is used in the example given above.

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