Occupant labeling for airbag-related applications

摘要

An invention is disclosed to divide a segmented image of an occupant into an upper torso image and a lower torso image. An occupant labeling heuristic can identify each pixel within the segmented image as an upper torso pixel or a lower torso pixel. A k-means module can provide an initial pixel classification by comparing the distance between the particular pixel and an estimated midpoint on the upper torso with the distance between the particular pixel and an estimated midpoint on the lower torso. The iterative parameters estimator can update the mean values for the upper torso and lower torso by performing a conditional likelihood heuristic. Pixels can then be classified as either upper or lower torso pixels by comparing a Mahalonobis distance for each torso. Airbag-related applications can then use the upper torso image to generate occupant characteristics relevant to airbag-related applications.