A key concern in Automatic Face Recognition (AFR) is the decrease of recognition performance as the quality of images decreases. This paper introduces a method to evaluate the impact of face pose variability on face recognition accuracy. Experiments were conducted using three leading commercial face recognition algorithms on data with poses from 0 to ±20 deg in each of the roll, pitch, and yaw directions per subject. Results indicate that roll variations has small effect on performance, while pitch and yaw variations produce a significant increase in error rates. More recent algorithms show better results at low pose variability.

Additional Metadata
Keywords AFR, Automatic face recognition, Biometric performance analysis, Biometric sample quality, Receiver operator curve
Persistent URL dx.doi.org/10.1504/IJBM.2012.049734
Journal International Journal of Biometrics
Citation
Asfaw, Y. (Yednek), Scott, G. (Guy), Pelletier, P. (Paul), & Adler, A. (2012). Method to evaluate pose variability in automatic face recognition performance. International Journal of Biometrics, 4(4), 373–387. doi:10.1504/IJBM.2012.049734