Publication

Abstract : Face swapping has been a thriving genre of work which primarily is associated with the replacement or substitution of one referral face on the face of the other person, be it by means of still images or in real time. This paper exhibits the research on Real-Time Face Swapping algorithm, using the reference image of the user and henceforth considering it as our input image instead of using a data set thereby working on a real time model by the use of the python open-source model of Computer Vision i.e., OpenCV. The input image facial features and attributes are extracted and are replaced to make the final resulting output through our model. The training of the model starts with learning the facial alignments and features to be able to recognize a face and extract its features before swapping it. Now, heading over to the process of image warping by the dissociation and partitioning of the user's face and its background. To increase the precision of the model, in the second part of parsing the face is performed to cancel out other features of the live image, hence the output is obtained. In this research, it was tried to bring accuracy and precision to the model by improving the condition of the image, editing out borders, and training it to a bunch of data for face recognition and correction. On analyzing it delivers the most subtle outputs alongside performing the tasks with the process including the analysis of our image and its output too. The model delivered is to improve the conditions of security, privacy, image capture, and entertainment purposes.