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

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.