Infrared face recognition: a comprehensive review of methodologies and databases

Automatic face recognition is an area with immense practical potential which includes a wide range of commercial and law enforcement applications. Hence it is unsurprising that it continues to be one of the most active research areas of computer vision. Even after over three decades of intense research, the state-of-the-art in face recognition continues to improve, benefitting from advances in a range of different research fields such as image processing, pattern recognition, computer graphics, and physiology. Systems based on visible spectrum images, the most researched face recognition modality, have reached a significant level of maturity with some practical success. However, they continue to face challenges in the presence of illumination, pose and expression changes, as well as facial disguises, all of which can significantly decrease recognition accuracy. Amongst various approaches which have been proposed in an attempt to overcome these limitations, the use of infrared (IR) imaging has emerged as a particularly promising research direction. This paper presents a comprehensive and timely review of the literature on this subject. Our key contributions are: (i) a summary of the inherent properties of infrared imaging which makes this modality promising in the context of face recognition, (ii) a systematic review of the most influential approaches, with a focus on emerging common trends as well as key differences between alternative methodologies, (iii) a description of the main databases of infrared facial images available to the researcher, and lastly (iv) a discussion of the most promising avenues for future research.Comment: Pattern Recognition, 2014. arXiv admin note: substantial text overlap with arXiv:1306.160

Forensic Face Recognition: A Survey

Beside a few papers which focus on the forensic aspects of automatic face recognition, there is not much published about it in contrast to the literature on developing new techniques and methodologies for biometric face recognition. In this report, we review forensic facial identification which is the forensic experts‟ way of manual facial comparison. Then we review famous works in the domain of forensic face recognition. Some of these papers describe general trends in forensics [1], guidelines for manual forensic facial comparison and training of face examiners who will be required to verify the outcome of automatic forensic face recognition system [2]. Some proposes theoretical framework for application of face recognition technology in forensics [3] and automatic forensic facial comparison [4, 5]. Bayesian framework is discussed in detail and it is elaborated how it can be adapted to forensic face recognition. Several issues related with court admissibility and reliability of system are also discussed. \ud Until now, there is no operational system available which automatically compare image of a suspect with mugshot database and provide result usable in court. The fact that biometric face recognition can in most cases be used for forensic purpose is true but the issues related to integration of technology with legal system of court still remain to be solved. There is a great need for research which is multi-disciplinary in nature and which will integrate the face recognition technology with existing legal systems. In this report we present a review of the existing literature in this domain and discuss various aspects and requirements for forensic face recognition systems particularly focusing on Bayesian framework