Acquiring high-resolution face images in outdoor environments: A master-slave calibration algorithm


Facial recognition at-a-distance in surveillance scenarios remains an open problem, particularly due to the small number of pixels representing the facial region. The use of pan-tilt-zoom (PTZ) cameras has been advocated to solve this problem, however, the existing approaches either rely on rough approximations or additional constraints to estimate the mapping between image coordinates and pan-tilt parameters. In this paper, we aim at extending PTZ-assisted facial recognition to surveillance scenarios by proposing a master-slave calibration algorithm capable of accurately estimating pan-tilt parameters without depending on additional constraints. Our approach exploits geometric cues to automatically estimate subjects height and thus determine their 3D position. Experimental results show that the presented algorithm is able to acquire high-resolution face images at a distance ranging from 5 to 40 meters with high success rate. Additionally, we certify the applicability of the aforementioned algorithm to biometric recognition through a face recognition test, comprising 20 probe subjects and 13,020 gallery subjects.

2015 IEEE 7th International Conference on Biometrics Theory, Applications and Systems, BTAS 2015 16 December 2015, Article number 7358744 7th IEEE International Conference on Biometrics Theory, Applications and Systems, BTAS 2015; Arlington; United States; 8 September 2015 through 11 September 2015; Category numberCFP15BTA-ART; Code 118731
Silvio Barra
Silvio Barra
Assistant Professor

Assistant Professor @ University of Naples