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Real-Time Nose Detection and Tracking Based on AdaBoost and Optical Flow Algorithms

  • D. González-Ortega
  • F. J. Díaz-Pernas
  • M. Martínez-Zarzuela
  • M. Antón-Rodríguez
  • J. F. Díez-Higuera
  • D. Boto-Giralda
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5788)

Abstract

In this paper we present a fast and robust nose detection and tracking application which runs on a consumer-grade computer with video input from an inexpensive Universal Serial Bus camera. Nose detection is based on the AdaBoost algorithm with Haar-like features. A detailed study was developed to select the positive and negative training samples and the parameters of the detector. Pyramidal Lucas-Kanade optical flow tracking algorithm is applied to the nostrils from a previous nose detection in a frame of a video sequence. Tracking takes 2 ms and is robust to different face positions, backgrounds and illumination. The nose detection and tracking application can be used alone or integrated in a hand-free vision-based Human-Computer Interface.

Keywords

Nose detection and tracking AdaBoost Pyramidal Lucas-Kanade optical flow 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • D. González-Ortega
    • 1
  • F. J. Díaz-Pernas
    • 1
  • M. Martínez-Zarzuela
    • 1
  • M. Antón-Rodríguez
    • 1
  • J. F. Díez-Higuera
    • 1
  • D. Boto-Giralda
    • 1
  1. 1.Department of Signal Theory, Communications and Telematics Engineering, Telecommunications Engineering SchoolUniversity of ValladolidValladolidSpain

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