A Wearable Face Recognition System on Google Glass for Assisting Social Interactions

Abstract

In this paper, we present a wearable face recognition (FR) system on Google Glass (GG) to assist users in social interactions. FR is the first step towards face-to-face social interactions. We propose a wearable system on GG, which acts as a social interaction assistant, the application includes face detection, eye localization, face recognition and a user interface for personal information display. To be useful in natural social interaction scenarios, the system should be robust to changes in face pose, scale and lighting conditions. OpenCV face detection is implemented in GG. We exploit both OpenCV and ISG (Integration of Sketch and Graph patterns) eye detectors to locate a pair of eyes on the face, between them the former is stable for frontal view faces and the latter performs better for oblique view faces. We extend the eigenfeature regularization and extraction (ERE) face recognition approach by introducing subclass discriminant analysis (SDA) to perform within-subclass discriminant analysis for face feature extraction. The new approach improves the accuracy of FR over varying face pose, expression and lighting conditions. A simple user interface (UI) is designed to present relevant personal information of the recognized person to assist in the social interaction. A standalone independent system on GG and a Client-Server (CS) system via Bluetooth to connect GG with a smart phone are implemented, for different levels of privacy protection. The performance on database created using GG is evaluated and comparisons with baseline approaches are performed. Numerous experimental studies show that our proposed system on GG can perform better real-time FR as compared to other methods.