Probabilistic Corner Detection for Facial Feature Extraction

Risultato della ricerca: Chapter

5 Citazioni (Scopus)

Abstract

After more than 35 years of resarch, face processing is considered nowadays as one of the most important application of image analysis. It can be considered as a collection of problems (i.e., face detection, normalization, recognition and so on) each of which can be treated separately. Some face detection and face recognition techniques have reached a certain level of maturity, however facial feature extraction still represents the bottleneck of the entire process. In this paper we present a novel facial feature extraction approach that could be used for normalizing Viola-Jones detected faces and let them be recognized by an appearance-based face recognition method. For each observed feature a prior distribution is computed and used as boost map to filter the Harris corner detector response producing more feature candidates on interest region while discarding external values. Tests have been performed on both AR and BioID database using approximately 1750 faces and experimental results are very encouraging.
Lingua originaleEnglish
Titolo della pubblicazione ospiteImage Analysis and Processing. ICIAP 2009
Pagine461-470
Numero di pagine10
Stato di pubblicazionePublished - 2009

Serie di pubblicazioni

NomeLECTURE NOTES IN COMPUTER SCIENCE

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • ???subjectarea.asjc.1700.1700???

Fingerprint Entra nei temi di ricerca di 'Probabilistic Corner Detection for Facial Feature Extraction'. Insieme formano una fingerprint unica.

Cita questo