As part of the U.S. Department of Transportations Intelligent Vehicle Initiative (IVI) program, the Federal
Highway Administration (FHWA) is conducting R&D in vehicle safety and driver information systems.
There is an increasing number of applications where pedestrian monitoring is of high importance. Visionbased
pedestrian detection in outdoor scenes is still an open challenge. People dress in very different colors
that sometimes blend with the background, wear hats or carry bags, and stand, walk and change directions
unpredictably. The background is various, containing buildings, moving or parked cars, bicycles, street signs,
signals, etc. Furthermore, existing pedestrian detection systems perform only during daytime, making it
impossible to detect pedestrians at night. Under FHWA funding, we are developing a multi-pedestrian
detection system using IR LED stereo camera. This system, without using any templates, detects the
pedestrians through statistical pattern recognition utilizing 3D features extracted from the disparity map. A
new IR LED stereo camera is being developed, which can help detect pedestrians during daytime and night
time. Using the image differencing and denoising, we have also developed new methods to estimate the
disparity map of pedestrians in near real time. Our system will have a hardware interface with the traffic
controller through wireless communication. Once pedestrians are detected, traffic signals at the street
intersections will change phases to alert the drivers of approaching vehicles. The initial test results using
images collected at a street intersection show that our system can detect pedestrians in near real time.