Skip to main content

On the Application of Heteroassociative Morphological Memories to Face Localization

  • Conference paper
  • First Online:
Bio-Inspired Applications of Connectionism (IWANN 2001)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2085))

Included in the following conference series:

Abstract

Face localization is a previous step for face recognition and in some circumstances has proven to be a difficult task. The Heteroassociative Morphological Memories are a recently proposed neural network architecture based on the shift of the basic algebraic framework. They possess some robustness to specific noise models (erosive and dilative noise). Here we show how they can be applied to the task of face localization.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. G.X. Ritter, P. Sussner and J.L. Diaz-de-Leon, IMorphological Associative Memories I, IEEE Trans. on Neural Networks, 9(2), (1998), pp. 281–292

    Article  Google Scholar 

  2. G.X. Ritter, J.L. Diaz-de-Leon and P. Sussner, IMorphological Bidirectional Associative MemoriesI, Neural Networks, Vol. 12, (1999), pp. 851–867

    Article  Google Scholar 

  3. Rowley H.A., Baluja S., Kanade T., Neural Network-Based Face Detection, IEEE Trans. Patt. Anal. Mach. Int., vol. 20,no.1, (1998), pp. 23–38

    Article  Google Scholar 

  4. Sung K.K., Poggio T., Example-Based Learning for View-Based Human Face Detection, IEEE Trans. Patt. Anal. Mach. Int., vol. 20,no.1, (1998), pp. 39–50

    Article  Google Scholar 

  5. Moghaddam B. and Pentland A., Probabilistic Visual Learning for Object Detection, Proc. of International Conference on Computer Vision, IEEE Press, (1995), pp. 786–793

    Google Scholar 

  6. Turk M., Pentland A., Eigenfaces for Recognition. Journal of Cognitive Neuroscience, vol. 3,no. 1, (1991), pp. 71–8

    Article  Google Scholar 

  7. Penev P.S., Atick J.J., Local Feature Analysis: A General Statistical Theory for Object Representation, Network:Computation in Neural Systems, vol. 7, (1996), pp.477–500

    Article  MATH  Google Scholar 

  8. Lin S.H., Kung S.Y., Lin L.J., Face Recognition/Detection by Probabilistic Decision-Based Neural Network, IEEE Trans. on Neural Networks, vol. 8,no. 1, (1997), pp. 114–132

    Article  Google Scholar 

  9. Juell P., Marsh R., A Hierarchical Neural Network for Human Face Detection, Pattern Recognition, vol. 29,no. 5, (1996), pp. 781–787

    Article  Google Scholar 

  10. Dai Y., Nakano Y., Recognition of Facial Images with Low Resolution Using a Hopfield Memory Model, Pattern Recognition, vol. 31,no. 2, (1998), pp. 159–167

    Article  Google Scholar 

  11. Takács B., Comparing Face Images Using the Modified Hausdorff Distance, Pattern Recognition, vol. 31,no. 12, (1998), pp. 1873–1881

    Article  Google Scholar 

  12. Marqués F., Vilaplana V., Buxes A., Human Face Segmentation and Tracking Using Connected Operators and Partition Projection, Proc. ICIP, 1999

    Google Scholar 

  13. Wang J., Tan T., A New Face Detection Method Based on Shape Information, Pattern Recognition Letters, vol. 21,no. 6-7, (2000), pp. 463–471

    Article  Google Scholar 

  14. Leung T.K., Burl M.C., Perona P., Finding Faces in Cluttered Scenes Using Random Labeled Graph Matching, Proc. of The Fifth ICCV, http://HTTP.CS.Berkeley.EDU/~leungt/Research/ICCV95_.nal.ps.gz, 1995

  15. Yow K.C., Cipolla R., Finding Initial Estimates of the Human Face Location, Technical Report TR-239, University of Cambridge, (1995)

    Google Scholar 

  16. Colombo C., Bimbo A.d., Real-Time Head Tracking from the Deformation of Eye Contours Using a Piecewise Affine Camera, Pattern Recognition Letters, vol. 20,no.7, (1999), pp. 721–730

    Article  Google Scholar 

  17. Lee C.H., Kim J.S., Park K.H., Automatic Human Face Location in a Complex Background Using Motion and Color Information, Pattern Recognition, vol. 29,no.11, (1996), pp. 1877–1889

    Article  Google Scholar 

  18. Yang G., Huang T.S., Human Face Detection in a Complex Background, Pattern Recognition, vol. 27,no. 1, (1994), pp. 53–63

    Article  Google Scholar 

  19. Yoo T.-W., Oh I.-S., A Fast Algorithm for Tracking Human Faces Based on Chromatic Histograms, Pattern Recognition Letters, vol. 20,no. 10, (1999), pp. 967–978

    Article  Google Scholar 

  20. McKenna S.J., Gong S., Raja Y., Modelling Facial Colour and Identity with Gaussian Mixtures, Pattern Recognition, vol. 31,no. 12, (1998), pp. 1883–1892

    Article  Google Scholar 

  21. saber E., Tekalp A.M., Frontal-View Face Detection and Facial Feature Extraction Using Color, Shape and Symmetry Based Cost Functions, Pattern Recognition Letters, vol. 19,no. 8, (1998), pp. 669–680

    Article  MATH  Google Scholar 

  22. Yin L., Basu A., Integrating Active Face Tracking with Model Based Coding, Pattern Recognition Letters, vol. 20,no. 6, (1999), pp. 651–657

    Article  Google Scholar 

  23. Wang J.-G., Sung E., Frontal-View Face Detection and Facial Feature Extraction Using Color and Morphological Operators, Pattern Recognition Letters, vol. 20,no.10, (1999), pp. 1053–1068

    Article  Google Scholar 

  24. Jackway P.T., Deriche M., Scale-Space Properties of the Multiscale Morphological Dilation-Erosion, IEEE Trans. on Patt Anal. and Mach. Int., vol. 18,no.1, (1996), pp. 38–516

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2001 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Raducanu, B., Graña, M. (2001). On the Application of Heteroassociative Morphological Memories to Face Localization. In: Mira, J., Prieto, A. (eds) Bio-Inspired Applications of Connectionism. IWANN 2001. Lecture Notes in Computer Science, vol 2085. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45723-2_68

Download citation

  • DOI: https://doi.org/10.1007/3-540-45723-2_68

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42237-2

  • Online ISBN: 978-3-540-45723-7

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics