Block-Based Search Space Reduction Technique for Face Detection Using Shoulder and Head Curves

  • Supriya Sathyanarayana
  • Ravi Kumar Satzoda
  • Suchitra Sathyanarayana
  • Srikanthan Thambipillai
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8333)


Conventional face detection techniques usually employ sliding window based approaches involving series of classifiers to accurately determine the position of the face in an input image resulting in high computational redundancy. Pre-processing techniques are being investigated to reduce the search space for face detection. In this paper, we propose a systematic approach to reduce the search space for face detection using head and shoulder curves. The proposed method includes Gradient Angle Histograms (GAH) that are applied in a block-based manner to detect these curves, which are further associated to determine the search space for face detection. A performance evaluation of the proposed method on the datasets (CASIA and Buffy) shows that an average search space reduction upto 80% is achieved with detection rates of over 90% for specific parameters of the dataset.


search space reduction face detection visual search face localization computational efficiency head and shoulder curve 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Supriya Sathyanarayana
    • 1
  • Ravi Kumar Satzoda
    • 1
  • Suchitra Sathyanarayana
    • 1
  • Srikanthan Thambipillai
    • 1
  1. 1.Nanyang Technological UniversitySingapore

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