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A landmark paper in face recognition
G.M. Beumer, Q. Tao, A.M. Bazen, and R.N.J. Veldhuis University of Twente, EEMSC, Signals and Systems P.O. box 217, 7500 AE, Enschede, The Netherlands [e-mail]

Abstract
Good registration (alignment to a reference) is essential for accurate face recognition. The effects of the number of landmarks on the mean localization error and the recognition performance are studied. Two landmarking methods are explored and compared for that purpose: (1) the Most Likely-Landmark Locator (MLLL), based on maximizing the likelihood ratio [2], and (2) Viola-Jones detection [14]. Both use the locations of facial features (eyes, nose, mouth, etc) as landmarks. Further, a landmark-correction method (BILBO) based on projection into a subspace is introduced. The MLLL has been trained for locating 17 landmarks and the Viola-Jones method for 5. The mean localization errors and effects on the verification performance have been measured. It was found that on the eyes, the Viola-Jones detector is about 1% of the interocular distance more accurate than the MLLL-BILBO combination. On the nose and mouth, the MLLL-BILBO combination is about 0.5% of the inter-ocular distance more accurate than the Viola-Jones detector. Using more landmarks will result in lower equal-error rates, even when the landmarking is not so accurate. If the same landmarks are used, the most accurate landmarking method will give the best verification performance. Keywords: face registration, face recognition, landmarking, likelihood ratio, Viola-Jones, landmark correction

In this paper1 we propose an improvement on earlier work by Bazen et al. [2] and a Viola-Jones based landmark finder. Both will be compared to each other and to groundtruth data. Their performances will be quantified by the RMS value of the error with respect to the groundtruth data. The equal-error rates (EERs) measured in a verification experiment measured by will be presented.

2. Landmark detection