Abstract

When an airbag deploys on a rear-facing infant seat, it can injure or kill the infant. When an airbag deploys on an empty seat, the airbag and the money to replace it are wasted. We have shown that video images can be used to determine whether or not to deploy the passenger-side airbag in a crash. Images of the passenger seat, taken from a video camera mounted inside the vehicle, can be used to classify the seat as either empty, containing a rear-facing infant seat, or occupied. Our first experiment used a single, monochrome video camera. The system was automatically trained on a series of test images. Using a principle components (eigenimages) nearest neighbor classifier, it achieved a correct classification rate of 99.5% on a test of 910 images. Our second experiment used a pair of monochrome video cameras to compute stereo disparity (a function of 3D range) instead of intensity images. Using a similar algorithm, the second approach achieved a correct classification rate of 95.1% on a test of 890 images. The stereo technique has the advantage of being less sensitive to illumination, and would likely work best in a real system.