Automatic Face Recognition System Using the Adaptive Clustering Network

摘要

We have developed an Automatic Face Recognition (AFR) System that uses theAdaptive Clustering Network (ACN)-a hybrid classifier that combines neural network learning with statistical decision making. The ACN automatically groups similar faces into the same cluster and creates new clusters for novel input faces. During training, the ACN updates the clusters continuously, and multiple clusters are created for the same subject to accommodate variations in the presentation of the subject's face (for example, changes in facial expression and/or head orientation). With incremental training, new subjects and further variations of existing subjects may be added on line without retraining the classifier on previous data. During the testing process, the ACN associates an input face with the cluster that most closely matches the face. The ACN minimizes misidentifications by reporting completely novel input faces as unknown.