| 摘要 |
A vision-based system for automatically detecting the type of object within a specified area, such as the type of occupant within a vehicle. Determination of the type of occupant can then be used to determine whether an airbag deployment system should be enabled or not. The system extracts different features from images captured by image sensors. These features are then processed by classification algorithms to produce occupant class confidences for various occupant types. The occupant class confidences are then fused and processed to determine the type of occupant. In a preferred embodiment, image features derived from image edges, motion, and range are used. Classification algorithms may be implemented by using trained C5 decision trees, trained Nonlinear Discriminant Analysis networks, Hausdorff template matching and trained Fuzzy Aggregate Networks. In an exemplary embodiment, class confidences are provided for a rear-facing infant seat, a front-facing infant seat, an adult out of position, and an adult in a normal or twisted position. Fusion of these class confidences derived from multiple image features increases the accuracy of the system and provides for correct determination of an airbag deployment decision. |
