Menu Content/Inhalt
Home arrow Technology Park arrow Video Surveillance

Video Surveillance

Computer Vision refers to the use of cameras and other input devices for computers to see like human.  Human needs the brain to interpret whatever images are captured by the eyes.  Similarly, computer needs software to interpret camera images. 

A modern video surveillance system deploys IP cameras to capture real life activities and a Video Management System (VMS) to interpret the images for human.  This system is already doing computer visioning although the context is mainly in physical security surveillance. 

Computer Vision is applicable to many walks of life than just security surveillance.  By recognising pattern of images, computers can tell if the pattern is a person, vehicle, or an object etc.  The algorithm is simple but computation can be tedious and accuracy would be doubtful.

Data modelling will be an ultimate means of analysing sequential static images.

The University of Auckland multimedia imaging website has this short introduction ( ):  Computer vision aims at understanding or modelling static or dynamic 3D objects or scenes based on captured image data. Typically it requires an understanding of projective geometry (how 3D objects are mapped into one or several 2D images, possibly from different perspectives), and combines (static) picture analysis with image sequence analysis. Image sequences are captured by normal video cameras or more advanced specialized cameras.

Return to Technology Park
September 2021 Horn Speaker Scares off Intruders (2021)
July 2020 Registration: Physical Security Systems health check
June 2020 Apartment Buildings
June 2020 System Health Program
June 2020 Residential Complex
June 2020 Queens Lodge, with 500+ apartment units & Retail complex
June 2020 Reference Sites
June 2020 Profile Sheets & Inspection Service
June 2020 Frequently Asked Questions
June 2020 Merits of Compucon IPVS Systems
June 2020 Compucon IPVS History
August 2013 Training note Video Analytics Counting
July 2013 Training Note Video Analytics Left Objects
July 2013 Training Note Video Analytics Human Behaviour
March 2013 Video Analytics versus IPVS 2013
March 2013 IP Cameras in 2013
April 2010 Video Analytics Flyer