Abstract
When a person passes by a surveillance camera a sequence of image is obtained. Before performing any analysis on the face of a person, the face first needs to be detected and secondary the quality of the different face images needs to be evaluated. In this paper we present a system based on four simple features including out-of-plan rotation, sharpness, brightness and resolution, to assess the face quality in a video sequence. These features are combined using both a local scoring system and weights. The system is evaluated on two databases and the results show a general agreement between the system output and quality assessment by a human.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Luo, H.: A Training-Based No-Reference Image Quality Assessment Algorithm. In: nternational Conference on image Processing (ICIP), pp. 2973–2976. IEEE Press, Los Alamitos (2004)
Subasic, M., Loncaric, S., Petkovic, T., Bogunvoic, H.: Face Image Validation System. In: 4th International Symposium on Image and Signal Processing and Analysis, pp. 30–36 (2005)
Fronthaler, H., Kollreider, K., Bigun, J.: Automatic Image Quality Assessment with Application in Biometrics. In: International Conference on Computer Vision and Pattern Recognition, IEEE Press, Los Alamitos (2006)
Xiufeng, G., Stan, Z., Rong, L., Zhang, P.: Standardization of Face Image Sample Quality. In: Lee, S.-W., Li, S.Z. (eds.) ICB 2007. LNCS, vol. 4642, pp. 242–251. Springer, Heidelberg (2007)
Fourney, A., Laganiere, R.: Constructing Face Image Logs that are Both Complete and Concise. In: 4th Canadian Conference on Computer Vision and Robot Vision, IEEE Press, Canada (2007)
Nasrollahi, K., Rahmati, M., Moeslund, T.B.: A Neural Network Based Cascaded Classifier for Face Detection in Color Images with Complex Background. In: Campilho, A., Kamel, M.S. (eds.) ICIAR 2008. LNCS, vol. 5112, pp. 966–976. Springer, Heidelberg (2008)
Peng, K., Chen, L., Ruan, S., Kukharev, G.: A Robust Algorithm for Eye Detection on Gray Intensity Face Without Spectacles. Journals of Computer Science and Technology 5(3), 127–132 (2005)
Weber, F.: Some quality measures for face images and their relationship to recognition performance. In: Biometric Quality Workshop. National Institute of Standards and Technology, Maryland, USA, March 8-9 (2006)
Solina, F., Peer, P., Batagelj, B., Juvan, S., Kovac, J.: Color-based face detection in the 15 seconds of fame art installation. In: Conference on Computer Vision / Computer Graphics Collaboration for Model-based Imaging, Rendering, image Analysis and Graphical special Effects, France, pp. 38–47 (2003)
Hermes project (FP6 IST-027110), http://www.cvmt.dk/projects/Hermes/index.html
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Nasrollahi, K., Moeslund, T.B. (2008). Face Quality Assessment System in Video Sequences. In: Schouten, B., Juul, N.C., Drygajlo, A., Tistarelli, M. (eds) Biometrics and Identity Management. BioID 2008. Lecture Notes in Computer Science, vol 5372. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89991-4_2
Download citation
DOI: https://doi.org/10.1007/978-3-540-89991-4_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-89990-7
Online ISBN: 978-3-540-89991-4
eBook Packages: Computer ScienceComputer Science (R0)