An online learning facial recognition method in the technical field of computation and calculation, and in particular the technical field of computer vision for facial recognition. The method comprises: training a face feature extractor by using an external data set, extracting a reference feature in a local data set corresponding to each member to construct a reference feature space, comparing a feature vector of a sample under test and the reference features to determine a reference feature most similar to the feature vector of the sample under test; if the reference feature most similar to the feature vector of the sample under test satisfies a threshold requirement, using, as the identity of the sample under test, a member identity to which the reference feature most similar to the feature vector of the sample under test belongs, and if not, returning a message indicating that the identity recognition of the sample under test has failed; updating the reference feature space according to the difference between a predicted feature vector of the sample under test and a corresponding actual feature vector thereof in the reference feature space. The invention adapts to changes in facial features that occur over time, and is especially applicable to situations in which the composition of members frequently changes.
ONLINE LEARNING FACIAL RECOGNITION METHOD