Disclaimer: The choice of the data sources reflects personal opinion of the Face Recognition Homepage administrators. Ranking used here should be treated as a guide-to-the-eye only. No comparison of the scientific merit of the included papers was intended.
Here you can find papers on face recognition that have more than 500 citations based on the SCOPUS or WoS databases. The below documents are sorted based on the number of citations according to SCOPUS database. Number of citations according to Google Scholar database are presented for completeness only. More information about the search conditions that were used to generate the results are presented below.
L. Torres, Is there any hope for face recognition?, Proc. of the 5th International Workshop on Image Analysis for Multimedia Interactive Services, WIAMIS 2004, 21-23 April 2004, Lisboa, Portugal
, 304 kB
L.-F. Chen, H.-Y.M. Liao, J.-C. Lin, C.-C. Han, Why Recognition in a Statistics-based Face Recognition System Should be based on the Pure Face Portion: a Probabilistic Decision-based Proof, Pattern Recognition, Vol.34, No.5, 2001, pp. 1393-1403
, 568 kB
R. Gross, J. Shi, J. Cohn, Quo vadis Face Recognition? - The current state of the art in Face Recognition, Technical Report, Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, USA, 25 pages
, 2.58 MB
R. Brunelli, T. Poggio, Face Recognition: Features versus Templates, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 15, No. 10, October 1993, pp. 1042-1052
This standard specifies definitions of photographic (environment, subject pose, focus, etc.) properties, digital image attributes and a face interchange format for relevant applications, including human examination and computer automated face recognition.
Along with researchers who focus on artificial intelligence and communication, Baltrusaitis has developed an open-source, facial-recognition software .
ISO/IEC 19794-5:2005 specifies scene, photographic, digitization and format requirements for images of faces to be used in the context of both human verification and computer automated recognition. The approach to specifying scene and photographic requirements in this format is to carefully describe constraints on how a photograph should appear rather than to dictate how the photograph should be taken. The format is designed to allow for the specification of visible information discernable by an observer pertaining to the face, such as gender, pose and eye colour. The digital image format can be either ISO standard JPEG or JPEG2000. Finally, the 'best practice' appendices provide guidance on photo capture for travel documents and face recognition performance versus digital compression.
R. Gross, S. Baker, I. Matthews, T. Kanade, Face Recognition Across Pose and Illumination, Handbook of Face Recognition, Stan Z. Li and Anil K. Jain, ed., Springer-Verlag, June, 2004, 27 pages
It is the general opinion that advances in computer vision research will provide useful insights to neuroscientists and psychologists into how human brain works, and vice versa. Psychology and neuroscience issues potentially interesting to face recognition system designers (according to Zhao et al. Survey, 2003) are:
- is face recognition a dedicated process?
- is face perception the result of holistic or feature analysis?
- ranking of significance of facial features;
- the role of spatial frequency analysis;
- view-point invariant recognition?
- effect of lighting change;
- movement and face recognition;
- facial expression.
We would like to encourage this kind of interdisciplinary approach. Here are some recent papers linking two areas and some psychology- and neuroscience-based face recognition papers.
P. Sinha, B. Balas, Y. Ostrovsky, R. Russell, Face Recognition by Humans: 19 Results All Computer Vision Researchers Should Know About, Proceedings of the IEEE, Vol. 94, No. 11, November 2006, pp. 1948-1962
We’re also looking at applications within medical scenarios. For example, it could help clinicians diagnose someone with psychosis by looking at their facial movements to determine whether they’re suffering from delusions or hallucinations. Facial-recognition software could provide doctors with objective measurements.