Reduced complexity Eye Detector for colour images using Harris Corners, Color heuristics and Edge maps

Eye detection plays a central role in automatic face detection systems and it is also important for human-computer interaction and face tracking. In this paper, we present a novel, unsupervised scheme for detecting eyes in skin patches based on our previous work on skin patch detection[l]. Working on the normalized RGB color space (NRGB), we use a combination of corner identification, color and edges as heuristics for detecting eyes. Experimental results show that our scheme is very fast in the AR and Champion databases (average time 2.53 and 0.21 seconds per image respectively with un-optimized code), while retaining very high detection rates (100 and 89.5% correspondingly).