Gender Recognition System Based on Human Face Picture

• Autorzy: Mazurkiewicz J.
• Języki publikacji: EN

Abstrakty

EN

The paper presents the analysis and discussion of gender recognition based on human face picture. The research combines different features selection techniques with the set of softcomputing classifiers. We are looking for not very complicated, fast and sensitive approach to create the theoretical basis for real safety systems where the correct “on-line” gender recognition is necessary. We start from the already known differences between the female and male face. This is the key point to tune the preprocessing mechanisms. We propose the quite classic classifiers, but we focus on sensible correlation between the feature extraction and the actual classification. The significant set of the results are discussed and the best solutions are pointed. All tests were realised based on the well known base of face pictures with added set of our own collection. The proposed solution can be an essential tool for the monitoring systems, safety guards and systems to point the dangerous situations based on video data.

Słowa kluczowe

EN

gender recognition; human face; safety system; picture analysis

• Wydawca: Polskie Towarzystwo Bezpieczeństwa i Niezawodności
• Czasopismo: Journal of Polish Safety and Reliability Association
• Rocznik: 2017
• Tom: Vol. 8, No. 1
• Strony: 97--104
• Opis fizyczny: Bibliogr. 9 poz., rys., tab., wykr.

Twórcy

autor

Mazurkiewicz J.

• Wroclaw University of Science and Technology, Faculty of Electronics, Poland

Bibliografia

• [1] Baluja, S. & Rowley, H., (2007). Boosting Sex Identification Performance. Int'l J. Computer Vision, 111-119.
• [2] Brunelli, R., Poggio, T. (1995). Hyberbf Networks for Gender Classification. Proceedings DARPA Image Understanding Workshop, 311–314.
• [3] Burton, A., Bruce, V. & Dench, N., (1993). What are the Differences between Men and Women? Evidence from Facial Measurement Perception.
• [4] Cottrell, G. & Metcalfe, J. (1990). Empath: Face, Emotions and Gender Recognition Using Holons. Neural Information Processing Systems, 564-571.
• [5] Golomb, B., Lawrence, D. & Sejnowski, T. (1991). Sexnet: A Neural Network Identifies Sex from Human Faces. Advance in Neural Information Processing Systems, 572-577.
• [6] http://www.nist.gov/itl/iad/ig/colorferet.cfm. Color FERET database.
• [7] Khan, S.A., Nazir, M., Riaz N. & Naveed, N., (2011). Computationally Intelligent Gender Classification Techniques: An Analytical Study. International Journal of Signal Processing, Image Processing and Pattern Recognition. Vol. 4, No. 4, 145-156.
• [8] Nazir, M., Ishtiaq, M., Batool, A., Jaffar, A. & Mirza, M., (2010). Feature Selection for Efficient Gender Classiffcation. WSEAS International Conference.
• [9] Shakhnarovich, G., Viola, P. & Moghaddam, B., (2002). A Unified Learning Framework for Real Time Faces Detection and Classiffication. IEEE Conference on Automatic Face and Gesture Recognition, 14-21.

Uwagi

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).