Adapting Hausdorff Metrics to Face Detection Systems: A Scale-Normalized Hausdorff Distance Approach

  • Pablo Suau
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3808)


Template matching face detection systems are used very often as a previous step in several biometric applications. These biometric applications, like face recognition or video surveillance systems, need the face detection step to be efficient and robust enough to achieve better results. One of many template matching face detection methods uses Hausdorff distance in order to search the part of the image more similar to a face. Although Hausdorff distance involves very accurate results and low error rates, overall robustness can be increased if we adapt it to our concrete application. In this paper we show how to adjust Hausdorff metrics to face detection systems, presenting a scale-normalized Hausdorff distance based face detection system. Experiments show that our approach can perform an accurate face detection even with complex background or varying light conditions.


Normalization Factor Face Detection Template Match Complex Background Video Surveillance System 
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.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Pablo Suau
    • 1
  1. 1.Departamento de Ciencia de la Computación e Inteligencia ArtificialUniversidad de AlicanteAlicanteSpain

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