Cameras talk to each other to track & spy on pedestrians
University of Washington electrical engineers have developed a way to automatically track people across moving and still cameras by using an algorithm that trains the networked cameras to learn one another’s differences. The cameras first identify a person in a video frame, then follow that same person across multiple camera views.
“Tracking humans automatically across cameras in a three-dimensional space is new,” said lead researcher Jenq-Neng Hwang, a UW professor of electrical engineering. “As the cameras talk to each other, we are able to describe the real world in a more dynamic sense.”
Frames from a moving camera recorded by the Swiss Federal Institute of Technology in Zurich, Switzerland, show how UW technology distinguishes among people by giving each person a unique color and number, then tracking them as they walk.Swiss Federal Institute of Technology
Hwang and his research team presented their results last month in Qingdao, China, at the Intelligent Transportation Systems Conference sponsored by the Institute of Electrical and Electronics Engineers, or IEEE.
Imagine a typical GPS display that maps the streets, buildings and signs in a neighborhood as your car moves forward, then add humans to the picture. With the new technology, a car with a mounted camera could take video of the scene, then identify and track humans and overlay them into the virtual 3-D map on your GPS screen. The UW researchers are developing this to work in real time, which could help pick out people crossing in busy intersections, or let DHS/ Police track a specific person.
“Our idea is to enable the dynamic visualization of the realistic situation of humans walking on the road and sidewalks, so eventually people can see the animated version of the real-time dynamics of city streets on a platform like Google Earth,” Hwang said.
Hwang’s research team has developed a way for video cameras – from the most basic models to high-end devices – to talk to each other as they record different places in a common location. The problem with tracking a human across cameras of non-overlapping fields of view is that a person’s appearance can vary dramatically in each video because of different perspectives, angles and color hues produced by different cameras.
The researchers overcame this by building a link between the cameras. Cameras first record for a couple of minutes to gather training data, systematically calculating the differences in color, texture and angle between a pair of cameras for a number of people who walk into the frames in a fully unsupervised manner without human intervention.
After this calibration period, an algorithm automatically applies those differences between cameras and can pick out the same people across multiple frames, effectively tracking them without needing to see their faces.
The tracking system first systematically picks out people in a camera frame, then follows each person based on his or her clothing texture, color and body movement.Swiss Federal Institute of Technology.
This detailed visual record is a wet dream come true for DHS/Police in the U.S. as they'll track your EVERY movement in real-time!
It also lets store owners and business proprietors spy on you in ways we've never dreamed of! It will send information and statistics about consumers’ moving patterns. A store owner could, for example, use a tracking system to watch a shopper’s movements in the store, taking note of his or her interests. Then, a coupon or deal for a particular product could be displayed on a nearby screen or pushed to the shopper’s phone – in an instant. Because you know they're spying on your smartphone as well, see video below: