A computer implemented method for enabling computer recognition of a particular person in images, comprising the steps of: analyzing a plurality of facial images of a person using a facial recognition model of the person to identify changes in facial appearance by comparing the facial images to the recognition model; calculating, in response to identifying changes in facial appearance between the facial images and the recognition model, subject recognition confidence values for the facial images, wherein calculating the subject recognition confidence values comprises using normalized ratios of probabilities calculated from similarity score distributions, wherein the similarity score distributions are probability distributions comprising a first distribution generated by computing similarity scores between the facial recognition model of the person and the plurality of facial images of the same person and a second distribution generated by computing the similarity scores between the facial recognition model of the person and a plurality of facial images from different persons; comparing the subject recognition confidence values for the facial images to prior subject recognition confidence values associated with the facial recognition model to identify changes in the confidence values; analyzing the identified changes in the subject recognition confidence values to determine whether a new facial recognition model is required for the person, wherein the step of analyzing the identified changes comprises tracking the decay in the subject recognition confidence values over time to identify significant changes in the confidence values; generating the new facial recognition model from current or subsequent images of the person if it is so determined by the step of analyzing the identified changes; and using the new facial recognition model for subsequent person recognition tasks. analyzing a plurality of facial images of a person using a facial recognition model of the person to identify changes in facial appearance by comparing the facial images to the recognition model; calculating, in response to identifying changes in facial appearance between the facial images and the recognition model, subject recognition confidence values for the facial images, wherein calculating the subject recognition confidence values comprises using normalized ratios of probabilities calculated from similarity score distributions, wherein the similarity score distributions are probability distributions comprising a first distribution generated by computing similarity scores between the facial recognition model of the person and the plurality of facial images of the same person and a second distribution generated by computing the similarity scores between the facial recognition model of the person and a plurality of facial images from different persons; comparing the subject recognition confidence values for the facial images to prior subject recognition confidence values associated with the facial recognition model to identify changes in the confidence values; analyzing the identified changes in the subject recognition confidence values to determine whether a new facial recognition model is required for the person, wherein the step of analyzing the identified changes comprises tracking the decay in the subject recognition confidence values over time to identify significant changes in the confidence values; generating the new facial recognition model from current or subsequent images of the person if it is so determined by the step of analyzing the identified changes; and using the new facial recognition model for subsequent person recognition tasks.