Single camera measures speed

One of the challenges of using cameras to give computers a way to see is finding a way to capture information about depth.

One approach is to, like biological stereo vision, triangulate from a pair of camera positions. There are practical drawbacks of this approach, however: double the camera equipment, double the power needs, and tricky calibration.

Researchers from Clemson University and the University of Florida have improved a method of determining depth information using a single camera.

The advance allows a single camera to detect the speed of objects and could be used anywhere robotic vision is needed. The method promises to decrease the cost of robotic vision and enable vision for applications like tiny flying robots.

It could also be used in place of a radar detector, according to the researchers. Unlike a radar detector, the camera could not be detected by motorists because it does not emit energy.

The camera calculates three-dimensional information from two-dimensional images based on three aspects of an object's movement: speed, acceleration and jerk. Jerk is, as the name implies, the smoothness of the motion. The method uses successive images to calculate an object's speed, and requires that the size of the object be estimated based on the distance between two parts of an object -- such as the wingtips of an airplane.

The researchers came up with the method by combining recent advances in image processing geometry and nonlinear mathematics. Nonlinear systems have outputs that are not proportional to the system's inputs. Previous methods of calculating the speed of an object using a single camera used the Kalman Filter, a technique that simplifies equations that describe the object and its motion. The researchers' advance replaces the Kalman Filter with a nonlinear estimation technique that does not simplify the underlying mathematics, according to the researchers.

The work appeared in the March 2005 issue of Automatica (Indication of a Moving Object's Velocity with a Fixed Camera).