Ohio State researchers works on panoramic video analytics project

Washington, Dec. 18 -- A 'smart' surveillance system that will help security watchdogs to recognize whether a person on the street is acting suspiciously or appears to be lost is being developed by engineers.

A team of engineers including James Davis and Karthik Sankaranarayanan from Ohio State University aims to develop a networked system of "smart" video cameras that will let surveillance officers observe a wide area quickly and efficiently. Computers will carry much of the workload.

"In my lab, we've always tried to develop technologies that would improve officers' situational awareness, and now we want to give that same kind of awareness to computers," said Davis, an associate professor of computer science and engineering at Ohio State University.

"We aim to analyse and model the behaviour patterns of people and vehicles moving through the scene, rather than attempting to determine the identity of people.

"We are trying to automatically learn what typical activity patterns exist in the monitored area, and then have the system look for atypical patterns that may signal a person of interest -- perhaps someone engaging in nefarious behaviour or a person in need of help," he added.

The engineers claim to have completed the first three phases of the project: they have one software algorithm that creates a wide-angle video panorama of a street scene, another that maps the panorama onto a high-resolution aerial image of the scene, and a method for actively tracking a selected target.

This software takes a series of snapshots from every direction within a camera's field of view, and combines them into a seamless panorama.

It creates a 360-degree high-resolution view of a camera's whole viewspace, as if someone were looking at the entire scene at once. The view resembles that of a large fish-eye lens.

As a person walks across a scene, the computer can calculate exactly where the person is on the panorama and aerial map. That information can then be used to instruct a camera to follow him or her automatically using the camera's pan-and-tilt control.

With this system, it will be possible for the computer to "hand-off" the tracking task between cameras as the person moves in and out of view of different cameras.

His team is now working on the next step in the research: determining who should be followed.

The system won't rely on traditional profiling methods, he said. A person's race or sex or general appearance won't matter. What will matter is where the person goes, and what they do.

"If you're doing something strange, we want to be able to detect that, and figure out what's going on," he said.

To first determine what constitutes normal behaviour, they plan to follow the paths of many people who walk through a particular scene over a long period of time. A line tracing each person's trajectory will be saved to a database.

Davis believes that system can also pick up people who are lost. "Humans can pick out a lost person really well," he said. "I believe you could build an algorithm that would also be able to do it."

Published by HT Syndication with permission from Asian News International.