Integrating Face Recognition into Security Systems

Automated processing of facial images has become a serious market for both hard- and software products. For the commercial success of face recognition systems it is most crucial that the process of face image capturing is very convenient for the people exposed to such systems. As a consequence, the whole imaging setup has to be carefully designed for each operational scenario.

[1]  C. Ponticos A Robust Real Time Face Location Algorithm for Videophones , 1993, BMVC.

[2]  R. Stephenson A and V , 1962, The British journal of ophthalmology.

[3]  Thomas S. Huang,et al.  Human face detection in a complex background , 1994, Pattern Recognit..

[4]  Roberto Brunelli,et al.  Face Recognition: Features Versus Templates , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  Trevor Darrell,et al.  Active face tracking and pose estimation in an interactive room , 1996, Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[6]  Ying Dai,et al.  Face-texture model based on SGLD and its application in face detection in a color scene , 1996, Pattern Recognit..

[7]  Rudolf Mai,et al.  Driver face recognition as a security and safety feature , 1995, Other Conferences.

[8]  Alexandros Eleftheriadis,et al.  Automatic Location Tracking of Faces and Facial Features in Video Sequences , 1995 .

[9]  Venu Govindaraju,et al.  Locating human faces in newspaper photographs , 1989, Proceedings CVPR '89: IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[10]  Thomas S. Huang,et al.  Facial feature extraction from color images , 1994, Proceedings of the 12th IAPR International Conference on Pattern Recognition, Vol. 3 - Conference C: Signal Processing (Cat. No.94CH3440-5).

[11]  Takeo Kanade,et al.  Neural network-based face detection , 1996, Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition.