Abstract: The present method relates to the automated indexing of event images for distribution. The automated indexing can use automated facial recognition to determine which people are in each image. The images indexed in this fashion can be presented in a gallery, ordered by characteristics of the people in the images such as their name or room number, so as to facilitate the selection of the images by the people. The identification of the people in the images can be assisted by security or other information regarding the people that may be available to the event manager. Furthermore, the closeness of the relationships of two people can be inferred from the degree to which the people are in the same images, allowing the people in the images to be placed into groups, which can be hierarchical and/or overlapping, and which can assist in the organization of images being presented to the people, either in a gallery or electronic display format.

Abstract: The present method relates to the automated indexing of event images for distribution. The automated indexing can use automated facial recognition to determine which people are in each image. The images indexed in this fashion can be presented in a gallery, ordered by characteristics of the people in the images such as their name or room number, so as to facilitate the selection of the images by the people. The identification of the people in the images can be assisted by security or other information regarding the people that may be available to the event manager. Furthermore, the closeness of the relationships of two people can be inferred from the degree to which the people are in the same images, allowing the people in the images to be placed into groups, which can be hierarchical and/or overlapping, and which can assist in the organization of images being presented to the people, either in a gallery or electronic display format.

Abstract: The present method relates to the manual assistance for the automated indexing (100) of a collection of images using facial recognition. In a first automated indexing step, automated indexing of faces within a collection of images is performed, creating sets of faces each of which comprises faces that are determined by the automated process to be representative of the same person. In a second splitting step (200), sets are displayed to an operator, who determines whether there are false-positive associations within a set. If false-positive associations are found, the faces representing different people are manually split into different sets, hi this way, there will be no false-positive associations within the collection of images, hi a third merging step (300), sets that have some degree of similarity are presented to the operator, who determines whether the two sets comprise representations of the same person. If so, the two sets are manually merged, thereby eliminating false-negative errors.