A biometric database with rotating head videos and hand- drawn face sketches

Authors:
Hanan A. Al Nizami;Jeremy P. Adkins-Hill;Yong Zhang;John R. Sullins;Christine McCullough;Shaun Canavan;Lijun Yin
Affiliations:
Department of Computer Science and Information Systems, Youngstown State University, Youngstown, OH;Department of Computer Science and Information Systems, Youngstown State University, Youngstown, OH;Department of Computer Science and Information Systems,Youngstown State University, Youngstown, OH;Department of Computer Science and Information Systems,Youngstown State University, Youngstown, OH;Department of Arts, Youngstown State University, Youngstown, OH;Department of Computer Science, State University of New York at Binghamton, Binghamton, NY;Department of Computer Science, State University of New York at Binghamton, Binghamton, NY
Venue:
BTAS'09 Proceedings of the 3rd IEEE international conference on Biometrics: Theory, applications and systems
Year:
2009

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Abstract

The past decade has witnessed a significant progress in biometric technologies, to a large degree, due to the availability of a wide variety of public databases that enable benchmark performance evaluations. In this paper, we describe a new database that includes: (i) Rotating head videos of 259 subjects; (ii) 250 hand-drawn face sketches of 50 subjects. Rotating head videos were acquired under both normal indoor lighting and shadow conditions. Each video captured four expressions: neutral, smile, surprise, and anger. For each subject, video frames of ten pose angles were manually labeled using reference images and empirical rules, to facilitate the investigation of multi-frame fusion. The database can also be used to study 3D face recognition by reconstructing a 3D face model from videos. In addition, this is the only currently available database that has a large number of face sketches drawn by multiple artists. The face sketches are valuable resource for many researches, such as forensic analysis of eyewitness recollection, impact assessment of face degradation on recognition rate, as well as comparative evaluation of sketch recognitions by humans and algorithms.