Object detection based on HOG features: Faces and dual-eyes augmented reality

Author

Hbali, Youssef ; Sadgal, Mohammed ; El Fazziki, Abdelaziz

Author_Institution

Fac. of Sci. Semlalia, Univ. of Cadi Ayyad, Marrakech, Morocco

fYear

2013

fDate

22-24 June 2013

Firstpage

1

Lastpage

4

Abstract

Histogram of oriented gradients have been widely used for classification, face detection and recognition. In this paper we present a virtual eye glasses try-on system based on augmented reality and HOG features for face and eyes detection. Machine learning algorithms are used for real time eyes tracking, the resulting face and eyes positions are continuously utilized to overlay the glasses image over the face. The system helps evaluating glasses before trying them in the store and makes possible the design of its own style.

Keywords

augmented reality; face recognition; gradient methods; image classification; learning (artificial intelligence); object detection; object tracking; real-time systems; HOG features; classification; dual-eyes augmented reality; eyes detection; eyes position; face detection; face position; face recognition; glasses image; histogram of oriented gradients; machine learning algorithms; object detection; real time eyes tracking; virtual eye glasses try-on system; Augmented reality; Boosting; Computer vision; Detectors; Feature extraction; Glass; Histograms;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer and Information Technology (WCCIT), 2013 World Congress on

Conference_Location

Sousse

Print_ISBN

978-1-4799-0460-0

Type

conf

DOI

10.1109/WCCIT.2013.6618716

Filename

6618716