A object (20) on a seat (16) of a motor vehicle (10) is classified by creating a video image of the area and forming a silhouette of the object. The silhouette is divided into two segments and a separate ellipse (64,66) is positioned to approximate the shape of each segment. The parameters that define the location and size of the two ellipses (64,66) form a feature vector for the object (20). A Bayesian classification function utilizes the feature vector to determine the probability that the object fits which each of a plurality of classes. A class for the object (20) is determined based on the probabilities. This method can be used to control operation of an air bag (24) in the motor vehicle (10) in response to the class of the object on the seat.
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