Face recognition using OpenCV
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MSc in Data Analytics
Dublin Business School
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Face recognition is one of the most useful contactless biometric identi cation tool, having several applications in security, surveillance and human-computer interactions etc. The concept of face recognition has been familiar in the Computer Vision community since long, but little development have been achieved due to challenges in feature engineering and achieving robustness (in terms of pose, illumination, occlusion etc.). However, with the inception of deep learning, most of these problems have been mitigated. But with all this improvents, deep learning models require a large amount of data and computational power to provide an accuracte model. In this work, we propose a face recognition pipeline based on deep learning architecture which can be trained with minimum number of samples without hours of training and can be implemented to run on videos in real time. Our method uses a pretrained deep learning framework based on the Inception module for feature generation, i.e. this module provides the feature vector for each face image. These features are used to train a Support Vector Machine (SVM) for classi cation. This architecture is validated on two large datasets (LFW and IMFDB).We have tested our model on videos, speci cally movie clips to access the model accuracy and speed. The achieved accuracy is above 91% with approximately 4-5 frames per second which proves the superority of our model. We have also provided a real life example of face recognition using our method with very few training images, and the achieved results are very promising. Finally, we have analysed the factors a ecting the end result and investigated some of our failure cases for better understanding.