An application of a bio-inspired visual attention model for the localization of vehicle parts
A two-step approach localizes vehicle parts using a bio-inspired visual attention. Bounding-boxes roughly locate parts of interest in the saliency map. Average bounding-box localization rates of 99.8% are obtained for different parts. Active contour models capture the boundaries of each vehicle part within each bounding box. A large number of parts can be identified in different views of a vehicle.
visual attention bio-inspired systems automotive vehicles vehicle part identification image classification active shape models