The recognition accuracy of 3 face recognition algorithms supported in mathematical spaceways (i.e., the Eigenfaces approach, the Fisher Faces technique, and the probabilistic Eigenfaces approach) is tested for various gallery sizes, image resolutions, and ranges of bits per pixel. Identical experiments are then conducted for numerous mixtures of these techniques, and the effectiveness of these mixtures is compared with that of the individual methods. The results show that there are some interesting relationships between recognition accuracy and image resolution. They also show that the mixtures of these techniques do improve performance over the individual approaches, which suggests that it might be worth looking into the unification of these approaches.