Video content analysis
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Video Analytics - also known as Video Content Analysis - is the science of analyzing video to detect and determine temporal events not based on a single image. It is used in a wide range of domains including entertainment, health care, retail, automotive, transport, domotica, safety and security. The algorithms can be implemented as software on general purpose machines, or as hardware in specialized video processing units.
Many different functionalities can be implemented in Video Analytics. Video Motion Detection is one of the simpler forms where motion is detected with regard to a fixed background scene. More advanced functionalities include video tracking and egomotion estimation.
Based on the internal representation that Video Analytics generates in the machine, it is possible to build other functionalities, such as identification, behavior analysis or other forms of situation awareness.
Video Analytics relies on good input video, so it is often combined with video enhancement technologies such as video denoising, image stabilization, unsharp masking and super-resolution.
Commercial applications
The quality of Video Analytics in the commercial setting is difficult to determine. It depends on many variables such as use case, implementation, system configuration and computing platform. Typical methods to get an objective idea of the quality in commercial settings include independent benchmarking[1] and designated test-locations. Video Analytics and Smart CCTV are commercial terms for "Video Content Analysis".
Academic Research
Video Content Analysis (the proper name for Video Analytics) is a subset of Computer Vision. Two major academic benchmark initiatives are TRECVID[2] and the PETS Benchmark Data[3]. They focus on functionalities such as tracking, left luggage detection and virtual fencing. Significant academic research into the field is ongoing at the LIVS, University of Calgary, University of Waterloo, University of Kingston, Georgia Institute of Technology, Carnegie Mellon University, and The British Columbia Institute of Technology.
References
- ^ i-Lids, Benchmarking initiative by the UK Home Office
- ^ TRECVID, Academic benchmark initiative by NIST
- ^ PETS Benchmark Data, Performance Evaluation of Tracking and Surveillance (PETS) by University of Reading
External links
- ipvideomarket.info: Commercial news outlet
- Demystifying video analytics - is "intelligent" now a dirty word?: Criteria to determine intelligence of video analytics solutions by Edward Troha, Director of Marketing for ObjectVideo
- Video Analytics: Understanding their limitations by Oliver Vellacott, CEO of IndigoVision
- Video analytics: the new magic solution? by Jeremy Kimber, Honeywell's EMEA Marketing Leader