Robust Real-Time Face Detection Using Hybrid Neural Networks

  • Ho-Joon Kim
  • Juho Lee
  • Hyun-Seung Yang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4115)


In this paper, a multi-stage face detection method using hybrid neural networks is presented. The method consists of three stages: preprocessing, feature extraction and pattern classification. We introduce an adaptive filtering technique which is based on a skin-color analysis using fuzzy min-max(FMM) neural networks. A modified convolutional neural network(CNN) is used to extract translation invariant feature maps for face detection. We present an extended version of fuzzy min-max (FMM) neural network which can be used not only for feature analysis but also for pattern classification. Two kinds of relevance factors between features and pattern classes are defined to analyze the saliency of features. These measures can be utilized to select more relevant features for the skin-color filtering process as well as the face detection process.


False Alarm Rate Face Detection Convolutional Neural Network Pattern Classifier Feature Range 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Garcia, C., Delakis, M.: Convolutional Face Finder: A Neural Architecture for Fast and Robust Face Detection. IEEE Transaction on Pattern Analysis and Machine Intelligence 26(11), 1408–1423 (2004)CrossRefGoogle Scholar
  2. 2.
    Lawrence, S., Giles, C.L., Tsoi, A.C., Back, A.D.: Face Detection: A Convolutional Neural-Network Approach. IEEE Transaction n Neural Networks 8(1), 98–113 (1997)CrossRefGoogle Scholar
  3. 3.
    Feraud, R., Bernier, O.J., Viallet, J.E., Collobert, M.: A Fast and Accurate Face Detector Based on Neural Networks. IEEE Transaction on Pattern Analysis and Machine Intelligence 23(1), 42–53 (2001)CrossRefGoogle Scholar
  4. 4.
    Hsu, R.-L., Abdel-Mottaleb, M., Jain, A.K.: Face Detection in Color Images. IEEE Transaction on Pattern Analysis and Machine Intelligence 24(5), 696–706 (2002)CrossRefGoogle Scholar
  5. 5.
    Zhu, Q., Cheng, K.T., Wu, C.T., Wu, Y.L.: Adaptive Learning of an Accurate Skin-Color Model. In: Proceeding of the Sixth IEEE International Conf. on Automatic Face and Gesture Recognitin, vol. 1 (2004)Google Scholar
  6. 6.
    Simpson, P.K.: Fuzzy Min-Max Neural Networks Part 1: Classification. IEEE Transaction on Neural Networks 3(5), 776–786 (1997)CrossRefMathSciNetGoogle Scholar
  7. 7.
    Kim, H.J., Ryu, T.W., Nguyen, T.T., Lim, J.S., Gupta, S.: A Weighted Fuzzy Min-Max Neural Network for Pattern Classification and Feature Extraction. In: Proceeding of International Conference on Computational Science and Its Application, Part.4, pp. 791–798 (2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Ho-Joon Kim
    • 1
  • Juho Lee
    • 2
  • Hyun-Seung Yang
    • 2
  1. 1.School of Computer Science and Electronic EngineeringHandong UniversityPohangKorea
  2. 2.Department of Computer ScienceKAISTDaejeonKorea

Personalised recommendations