SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
Detecting Faces in Images: A Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust Face Detection Using the Hausdorff Distance
AVBPA '01 Proceedings of the Third International Conference on Audio- and Video-Based Biometric Person Authentication
A General Framework for Object Detection
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Robust Real-Time Face Detection
International Journal of Computer Vision
An introduction to ROC analysis
Pattern Recognition Letters - Special issue: ROC analysis in pattern recognition
Reliable Face Recognition Methods: System Design, Implementation and Evaluation (International Series on Biometrics)
A geometric approach to face detector combining
MCS'11 Proceedings of the 10th international conference on Multiple classifier systems
Hi-index | 0.00 |
Face detection (FD) is widely used in interactive user interfaces, in advertising industry, entertainment services, video coding, is necessary first stage for all face recognition systems, etc. However, the last practical and independent comparisons of FD algorithms were made by Hjelmas et al. and by Yang et al. in 2001. The aim of this work is to propose parameters of FD algorithms quality evaluation and methodology of their objective comparison, and to show the current state of the art in face detection. The main idea is routine test of the FD algorithm in the labeled image datasets. Faces are represented by coordinates of the centers of the eyes in these datasets. For algorithms, representing detected faces by rectangles, the statistical model of eyes' coordinates estimation was proposed. In this work the seven face detection algorithms were tested; article contains the results of their comparison.