A study of face recognition of identical twins by humans

Recent studies have shown that face recognition performance degrades considerably for images of identical twins. Human face matching capability is often considered as a benchmark for assessing and improving automatic face recognition algorithms. In this work, we investigate human capability to distinguish between identical twins. If humans are able to distinguish between facial images of identical twins, it would suggest that humans are capable of identifying discriminating facial traits that can potentially be useful to develop algorithms for this very challenging problem. Experiments with different viewing times and imaging conditions are conducted to determine if humans viewing a pair of facial images can perceive if the image pairs belong to the same person or to a pair of identical twins. The experiments are conducted on 186 twin subjects, making it the largest such study in the literature to date. We observe that humans can perform the task significantly better if they are given enough time and tend to make more mistakes when images differ in imaging conditions. Our analysis also suggests that humans look for facial marks like moles, scars, etc. to make their decision and do worse when presented with images lacking such marks. Experiments with automatic face recognition systems show that human observers outperform automatic matchers for this task.