Automatic Eye Localization; Multi-block LBP vs. Pyramidal LBP Three-Levels Image Decomposition for Eye Visual Appearance Description

• Type: Article in International Conference Proceedings Book
• Date: 2015

Authors

Benrachou, DE (Author) Other; Filipe Neves Santos (Author) FEUP; Boulebtateche, B (Author) Other; Bensaoula, S (Author) Other

Conference proceedings International

Title: PATTERN RECOGNITION AND IMAGE ANALYSIS (IBPRIA 2015)

Pages: 718-726

7th Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA)

Santiago de Compostela, SPAIN, JUN 17-19, 2015

Indexing

ISI Web of Knowledge - 1 Citation

Scopus - 0 Citations

Other information

Authenticus ID: P-00G-EF9

DOI: 10.1007/978-3-319-19390-8_80

Abstract (EN): This manuscript presents the performance evaluation of our algorithm that precisely finds human eyes in still gray-scale images and describes the state of the founded eye. This algorithm has been evaluated considering two descriptors - Pyramid transform domain (PLBP) and Multi-Block Histogram LBP (BHLBP), which are extended versions of the Local Binary Pattern descriptor (LBP). For the classification stage, two types of supervised learning techniques have also been evaluated, Support Vector Machine (SVM) and Multilayer Perceptron (MLP). The proposed method is assessed on the Face Recognition Grand Challenge (BioID) and (CAS-PEAL-R1) databases, and experimental results demonstrate improved performance than some state-of-the-art eye detection approaches.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 9