Details

Autor(en) / Beteiligte

• Moghaddam, Baback
• Jebara, Tony
• Pentland, Alex

Titel

Bayesian face recognition

Ist Teil von

• Pattern recognition, 2000-11, Vol.33 (11), p.1771-1782

Ort / Verlag

Elsevier Ltd

Erscheinungsjahr

2000

Quelle

Elsevier Journal Backfiles on ScienceDirect (DFG Nationallizenzen)

Beschreibungen/Notizen

• We propose a new technique for direct visual matching of images for the purposes of face recognition and image retrieval, using a probabilistic measure of similarity, based primarily on a Bayesian (MAP) analysis of image differences. The performance advantage of this probabilistic matching technique over standard Euclidean nearest-neighbor eigenface matching was demonstrated using results from DARPA's 1996 “FERET” face recognition competition, in which this Bayesian matching alogrithm was found to be the top performer. In addition, we derive a simple method of replacing costly computation of nonlinear (on-line) Bayesian similarity measures by inexpensive linear (off-line) subspace projections and simple Euclidean norms, thus resulting in a significant computational speed-up for implementation with very large databases.