Light pipes track motion

By Eric Smalley, Technology Research News

Researchers at Duke University have devised a simple tracking method that promises to dramatically reduce the computing resources needed for computer vision systems that allow computers and robots to sense their surroundings.

The technique bridges the gap between full-blown computer vision systems, which precisely track moving objects but are computer-intensive, and simple, inexpensive motion detectors, which are much less precise.

Traditional computer vision systems use relatively sophisticated software and camera equipment; they are also limited to fairly simple models of physical space-camera relationships, said David Brady, a professor of electrical and computer engineering at Duke University.

The researchers' method dispenses with the complicated software and lenses and instead maps the angles of light radiating from a source by channeling the light through set of pipes onto a set of light detectors. As an object moves across the field of view, light reflecting from the object triggers some detectors but not others.

The method relies on a rapid prototyping system, which uses computer-controlled lasers to harden liquid plastic or fuse powdered metal, to make a custom set of pipes. The researchers calculate the necessary pipe angles for a certain task and use the rapid prototyping system to produce the structure.

The researchers made a prototype that monitored a moving light source at a distance of three meters. The 25.2-millimeter prototype has eight viewing angles, eight detectors and 36 pipes. Each pipe channels light from a given angle to a detector. Seven of the eight detectors monitor four angles and the remaining one monitors all eight. Each of the eight viewing angles spans five degrees, giving the device a 40-degree field of view.

When an object is in one position within the field of view, for example, it triggers detectors five, six, seven and eight, and when it moves to the next position it triggers detectors three, four, six and eight. A computer controlling the device simply has to know which combination of triggered detectors corresponds to which position.

In contrast, computer vision systems analyze every pixel in each digital video frame -- usually 15 to 30 frames per second -- to determine the borders of objects in the scene. The software tracks motion by comparing from one frame to the next the position of an object's pixels relative to background pixels.

At the other end of the scale, motion detectors like those that turn on backyard lights simply detect motion and don't track the positions of objects. They detect rapid changes in the intensity of infrared light hitting first one and then the other of a pair of side-by-side light detectors. The infrared light is typically produced by the heat of a human body, and the sequential triggering of the detectors is typically caused by a person moving across the motion detector's field of view.

The separate angles of the field of view through the researchers' structure allow for basic digital representations of moving objects, and the relatively low-tech detector array cuts down the amount of information a computer must sift through, according to Brady. "These sensors may be capable of reducing the data load in tracking... systems by several orders of magnitude," he said.

The lightened computational load could make object tracking much cheaper. The researchers are working on using the method to track vehicles and people in real-time, and have produced a prototype that tracks cars at a distance of 15 meters. "The sensors may also be useful in developing spatially-aware robots," said Brady.

The researchers are working with commercial partners to develop simple motion tracking systems using the technology, according to Brady. The system should be ready for practical use in the next year, he said.

Brady's research colleagues were Prasant Potuluri, Unnikrishnan Gopinathan and James R. Adelman. The work appeared in the April 21, 2003 issue of Optics Express. The research was funded by the Defense Advanced Research Projects Agency (DARPA).

Timeline:   1 year
Funding:   Government
TRN Categories:   Computer Vision and Image Processing
Story Type:   News
Related Elements:  Technical paper, "Lensless Sensor System Using a Reference Structure," April 21, 2003, Optics Express.


July 2/9, 2003

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