Evaluation of Haar Cascade Classifiers Designed for Face Detection

Authors: R. Padilla, C. F. F. Costa Filho, M. G. F. Costa

Abstract:

In the past years a lot of effort has been made in the field of face detection. The human face contains important features that can be used by vision-based automated systems in order to identify and recognize individuals. Face location, the primary step of the vision-based automated systems, finds the face area in the input image. An accurate location of the face is still a challenging task. Viola-Jones framework has been widely used by researchers in order to detect the location of faces and objects in a given image. Face detection classifiers are shared by public communities, such as OpenCV. An evaluation of these classifiers will help researchers to choose the best classifier for their particular need. This work focuses of the evaluation of face detection classifiers minding facial landmarks.

Keywords: Face datasets, face detection, facial landmarking, haar wavelets, Viola-Jones detectors.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1058133

References:

[1] J. Fagertun, 2005. Face Recognition. Master Thesis, Technical University of Denmark (DTU).
[2] Y. Gang, L. Jiawei, L. Jiayu, M. Qingli and Y. Ming, "Illumination Variation in Face Recognition: A Review", IEEE Second International Conference on Intelligent Networks and Intelligent Systems (ICINIS 2009), pp. 309-311.
[3] M.A. Turk, A.P. Pentland, "Face Recognition Using Eigenfaces", Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR-91), 3-6 June 1991, Maui, Hawaii, USA, pp. 586- 591.
[4] H. Moon, P.J. Phillips, "Computational and Performance Aspects of PCA-based Face Recognition Algorithms", Perception, Vol. 30, 2001, pp. 303-321.
[5] K. Etemad, R. Chellappa, "Discriminant Analysis for Recognition of Human Face Images", Journal of the Optical Society of America A, Vol. 14, No. 8, August 1997, pp. 1724-1733.
[6] J. Lu, K.N. Plataniotis, A.N. Venetsanopoulos, "Face Recognition Using LDA-Based Algorithms", IEEE Transaction on Neural Networks, Vol. 14, No. 1, January 2003, pp. 195-200.
[7] B. Heisele, P. Ho, T. Poggio, "Face Recognition with Support Vector Machines: Global versus Component-based Approach", Proceedings. of the Eighth IEEE International Conference on Computer Vision (ICCV-01), Vol. 2, 09-12 July 2001, Vancouver, Canada, pp. 688-694.
[8] A. Lanitis, C.J. Taylor, T.F. Cootes, "Automatic Interpretation and Coding of Face Images Using Flexible Models", IEEE Transaction Pattern Analysis and Machine Intelligence (1997), pp. 743-756.
[9] E. Gomathi, K. Baskaran, "Recognition of Faces Using Improved Principal Component Analysis", Second International Conference on Machine Learning and Computing (ICMLC-10), pp.198-201.
[10] C. Liu and H. Wechsler, "Probabilistic Reasoning Models for Face Recognition", in. IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR-98), pp.827-832.
[11] Y. Ji, T. Lin, and H. Zha, "Mahalanobis Distance Based Non-negative Sparse Representation for Face Recognition", in Proceedings The Eighth International Conference on Machine Learning and Applications (ICMLA-09), pp.41-46.
[12] V. Kabeer & N. K. Narayanan, "Face recognition using state space parameter and Artificial Neural Network Classifier", Proceedings of IEEE International Conference on Computational Intelligence and Multimedia Applications (ICCIMA-07), Sivakasi, India Vol.3, December, 2007, pp 250-254.
[13] M. Castrill├│n, O. Déniz, D. Hern├índez, and J. Lorenzo. "A Comparison of Face and Facial Feature Detectors based on the Viola-Jones General Object Detection Framework". Machine Vision and Applications, vol. 22 issue 3, 2011.
[14] P. N. Bellhumer, J. Hespanha, and D. Kriegman, "Eigenfaces vs. fisherfaces: Recognition using class specific linear projection", IEEE Transactions on Pattern Analysis and Machine Intelligence, Special Issue on Face Recognition, 1997, pp. 711-720.
[15] C. Thomaz and G. Giraldi, "A new ranking method for principal components analysis and its application to face image analysis", Journal Image and Vision Computing, 2010, vol. 28, no. 6, pp. 902-913.
[16] P. Viola and M. Jones, "Robust real-time object detection," International Journal of Computer Vision, 2002 vol. 57, no. 2, pp. 137- 154.
[17] Inte, Intel Open Source Computer Vision Library, v1. 1ore, http://sourceforge.net/projects/opencvlibrary (October 2011).
[18] Lienhart, R., Kuranov, A., Pisarevsky, V., "Empirical Analysis of Detection Cascades of Boosted Classifiers for Rapid Object Detection", in 25th Pattern Recognition Symposium (DAGM-03), pp. 297-304.
[19] Lienhart, R., Liang, L., Kuranov, A., "A Detector Tree of Boosted Classifiers for Real-Time Object Detection and Tracking", in IEEE International Conference on Multimedia and Expo (ICME-03), pp. 277-280.
[20] Wilson, P. I., Fernandez, J., "Facial feature detection using haar classifiers", in Journal of Computing Sciences in Colleges (2006), pp. 127-133.
[21] Bradley, D. "Profile face detection" http://www.cs.cmu.edu/ ~dbradley/publications/bradley-iurac-03.swf, (2003) last accessed 12/10/2011.
[22] Kruppa, H., Castrill├│n Santana, M., Schiele, B., "Fast and Robust Face Finding via Local Context", in IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance (VS-PETS-03), pp. 157-164.
[23] G. M. Beumer, Q. Tao, A. M. Bazen and R. N. J. Veldhuis, "A Landmark Paper in Face Recognition". IEEE International Conference on Automatic Face and Gesture Recognition (FGE-02), pp. 73-78.
[24] M. Koestinger, P. Wohlhart, P. M. Roth and H. Bischof, "Annotated Facial Landmarks in the Wild: A Large-scale, Real-world Database for Facial Landmark Localization", IEEE International Workshop on Benchmarking Facial Image Analysis Technologies (BeFIT-11).
[25] M. Jian-Wei and F. Yu-Hua, "Face segmentation algorithm based on ASM", IEEE Conference on Intelligent Computing and Intelligent Systems (ICIS-09), 2009, pp 495-499.
[26] Z. Liu, W. Li, X. Zhang and J. Yang, "Efficient Face Segmentation Based on Face Attention Model and Seeded Region Merging", 9th International Conference on Signal Processing (ICSP-08). pp. 1116- 1119.
[27] A.M. Martinez and R. Benavente, "The AR Face Database", CVC Technical Report #24, June - 1998.