MULTIPASS DATA INTEGRATION FOR AUTOMATIC DETECTION AND CLASSIFICATION OF OBJECTS

摘要

Classification of a potential target is accomplished by receiving image information, detecting a potential target within the image information and determining a plurality of features forming a feature set associated with the potential target. The location of the potential target is compared with a detection database to determine if it is close to an element in the detection database. If not, a single-pass classifier receives a potential target's feature set, classifies the potential target, and transmits the location, feature set and classification to the detection database. If it is close, a fused multi-pass feature determiner determines fused multi-pass features of the potential target and a multi-pass classifier receives the potential target's feature set and fused multi-pass features, classifies the potential target, and transmits its location, feature set, fused multi-pass features and classification to the detection database.