Perform face recognition of faces with superimposed facemasks using VGGFace2 in Keras. This post forms part of the continued work from the previous article - Facial mask overlay with OpenCV-dlib.
In this article, we will attempt to perform face detection on the “masked” face that has been generated using OpenCV and dlib library using MTCNN (Multi-task Cascaded Convolutional Networks). Thereafter, we will perform face recognition tests on the “masked” face using VGGFace2 in Keras.
We will also be testing our “masked” faces using Deep Learning model to determine if our “masking” of faces is successful. …
Superimpose facemasks using OpenCV-dlib library
Face masks have been shown to be one of the best defense against the spread of COVID-19. However, this has also led to the failure of facial recognition algorithms which are built around facial features including nose, mouth and jawline. Before the global pandemic, facial recognition systems verify faces in two images by performing comparison measurements between different facial features detected. The wearing of a mask over a person’s nose, mouth and cheeks, has greatly reduced the information normally used to figure out his/her identity.
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