Two-dimensional (2D) discrimination analysis using methods such as 2D PCA and Image LDA is of interest in face recognition because it extracts discriminative features faster than one-dimensional (1D) discrimination analysis. However, existing 2D methods generally use more discriminative features and
โฆ LIBER โฆ
RegionBoost learning for 2D+3D based face recognition
โ Scribed by Loris Nanni; Alessandra Lumini
- Publisher
- Elsevier Science
- Year
- 2007
- Tongue
- English
- Weight
- 588 KB
- Volume
- 28
- Category
- Article
- ISSN
- 0167-8655
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This paper presents an online learning approach to video-based face recognition that does not make any assumptions about the pose, expressions or prior localization of facial landmarks. Learning is performed online while the subject is imaged and gives near realtime feedback on the learning status.