Indigovision Releases Ip Video Integrated Analytics

Real time analytics are located at the edge of the network, i.e. at the camera, making the solution totally scalable. CCTV operators can now detect events as they happen such as congestion, stolen objects, cars parked too long outside a building, people moving the wrong way through security checkpoints, etc. “IndigoVision’s goal is to provide sophisticated analytics as an integral part of our IP Video management solution,” said Dr Oliver Vellacott, CEO. “Automating the real time detection of incidents frees up valuable operator resource and having the same set of tools available to analyze large volumes of recorded footage dramatically reduces the time to locate critical events, enabling timely response to emergency situations.” IndigoVision’s new analytics include: Congestion Detection, Motion Detection, Abandoned Object Detection, Counter Flow, Virtual Tripwire, Shape-Based Detection, Object Tracking and Theft Detection. All of these can be run in real-time at the camera or post-event on recorded video. Real time analytics run in the 8000 Transmitters connected to analogue cameras and in IndigoVision’s dedicated high-end IP domes. This significantly reduces bandwidth requirements on the network and ensures the system is totally scalable.  Pre-determined events are identified as they happen, at any camera, and can drive the virtual matrix, e.g. display a salvo on a bank of monitors. Real-time analytics lead to increased effectiveness and improvements in incident detection hit rates. Using ‘Control Center’ software, recorded footage stored on IndigoVision’s networked video recorders (NVRs) can be analysed using the same algorithms. Post processing allows operators to run many different scenarios on recorded video, e.g. look for cars parked for a certain time.  Enabling analytics in both real-time and post-event modes offers the best of both worlds, using analytics to identify events as they occur, and also providing advanced search tools for operators to analyse previous situations.