Evaluation of image resolution and super-resolution on face recognition performance

While researchers strive to improve automatic face recognition performance, the relationship between image resolution and face recognition performance has not received much attention. This relationship is examined systematically and a framework is developed such that results from super-resolution techniques can be compared. Three super-resolution techniques are compared with the Eigenface and Elastic Bunch Graph Matching face recognition engines. Parameter ranges over which these techniques provide better recognition performance than interpolated images is determined.

► We evaluate the impact of image resolution on face recognition performance.
► We evaluate the impact of super-resolution on face recognition performance.
► Three super-resolution methods are compared with common face recognition engines.
► We provide an evaluation framework to conduct a resolution impact analysis.
► Super-resolution improves recognition with low-resolution and noisy facial images.