Experimental Analysis of Face Recognition on Still and CCTV Images

Although automatic identity inference based on faces has shown success when using high quality images, for CCTV based images it is hard to attain similar levels of performance. Furthermore, compared to recognition based on static images, relatively few studies have been done for video based face recognition. In this paper, we present an empirical analysis and comparison of face recognition using high quality and CCTV images in several important aspects: image quality (including resolution, noise, blurring and interlacing) as well as geometric transformations (such as translations, rotations and scale changes). The results show that holistic face recognition can be tolerant to image quality degradation but can also be highly influenced by geometric transformations. In addition, we show that camera intrinsics have much influence - when using different cameras for collecting gallery and probe images the recognition rate is considerably reduced. We also show that the classification performance can be considerably improved by straightforward averaging of consecutive face images from a CCTV video sequence.

[1]  J.-J. Wang,et al.  Face Image Resolution versus Face Recognition Performance Based on Two Global Methods , 2004 .

[2]  A. O'Toole,et al.  Recognizing moving faces: a psychological and neural synthesis , 2002, Trends in Cognitive Sciences.

[3]  B. Lovell,et al.  Illumination and expression invariant face recognition with one sample image , 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..

[4]  Matti Pietikäinen,et al.  From still image to video-based face recognition: an experimental analysis , 2004, Sixth IEEE International Conference on Automatic Face and Gesture Recognition, 2004. Proceedings..

[5]  Samy Bengio,et al.  On transforming statistical models for non-frontal face verification , 2006, Pattern Recognit..

[6]  Mislav Grgic,et al.  Generalization Abilities of Appearance-Based Subspace Face Recognition Algorithms , 2005 .

[7]  Wen Gao,et al.  Virtual face image generation for illumination and pose insensitive face recognition , 2003, 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)..

[8]  A. M. Burton,et al.  100% Accuracy in Automatic Face Recognition , 2008, Science.

[9]  David White,et al.  Face Recognition from Unconstrained Images: Progress with Prototypes , 2006, 7th International Conference on Automatic Face and Gesture Recognition (FGR06).

[10]  Hyeonjoon Moon,et al.  The FERET Evaluation Methodology for Face-Recognition Algorithms , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[11]  Ronen Basri,et al.  Lambertian Reflectance and Linear Subspaces , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[12]  Jim Austin,et al.  Three-dimensional face recognition: an eigensurface approach , 2004, 2004 International Conference on Image Processing, 2004. ICIP '04..

[13]  K. Walker,et al.  View-based active appearance models , 2000, Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580).

[14]  B. V. K. Vijaya Kumar,et al.  Face authentication for multiple subjects using eigenflow , 2003, Pattern Recognit..

[15]  Shimon Ullman,et al.  Face Recognition: The Problem of Compensating for Changes in Illumination Direction , 1994, IEEE Trans. Pattern Anal. Mach. Intell..

[16]  Brian C. Lovell,et al.  Towards Pose-Invariant 2D Face Classification for Surveillance , 2007, AMFG.

[17]  Zezhi Chen,et al.  Face Recognition: A Comparison of Appearance-Based Approaches , 2003, DICTA.

[18]  Chengjun Liu,et al.  Probabilistic reasoning models for face recognition , 1998, Proceedings. 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No.98CB36231).

[19]  Brian C. Lovell,et al.  Face Recognition Robust to Head Pose from One Sample Image , 2006, 18th International Conference on Pattern Recognition (ICPR'06).

[20]  Rama Chellappa,et al.  Probabilistic recognition of human faces from video , 2002, Proceedings. International Conference on Image Processing.

[21]  C. Liu,et al.  Face recognition is robust with incongruent image resolution: relationship to security video images. , 2003, Journal of experimental psychology. Applied.