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On the Combination of Different Template Matching Strategies for Fast Face Detection

  • Bernhard Fröba
  • Walter Zink
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2096)

Abstract

Computer-based face perception is becoming increasingly important for many applications like biometric face recognition, video coding or multi-model human-machine interaction. Fast and robust detection and segmentation of a face in an unconstrained visual scene is a basic requirement for all kinds of face perception. This paper deals with the integration of three simple visual cues for the task of face detection in grey level images. It is achieved by a combination of edge orientation matching, hough transform and an appearance based detection method. The proposed system is computationally efficient and has proved to be robust under a wide range of acquisition conditions like varying lighting, pixel noise and other image distortions. The detection capabilities of the presented algorithm are evaluated on a large database of 13122 images including the frontal-face set of the m2vts database. We achieve a detection rate of over 91% on this database while having only few false detects at the same time.

Keywords

Face Image Gesture Recognition Edge Orientation Edge Strength Face Position 
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 2001

Authors and Affiliations

  • Bernhard Fröba
    • 1
  • Walter Zink
    • 1
  1. 1.Departement of Applied ElectronicsFraunhofer Institute for Integrated CircuitsErlangenGermany

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