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Extraction of an image in order to apply face recognition methods

Abstract : The aim of this thesis is to create a methodology in order to extract one or a few representative face images of a video sequence with a view to apply a face recognition algorithm. A video is a media particularly rich. Among all the objects present in the video, human faces are, for sure, the most salient objects. Let us consider a video sequence where each frame contains a face of the same person. The primary assumption of this thesis is that some samples of this face are better than the others in terms of face recognition. A face is a non-rigid 3D object that is projected on a plan to form an image. Hence, the face appearance changes according to the relative positions of the camera and the face. Many works in the field of face recognition require faces as frontal as possible. To extract the most frontal face samples, on the one hand, we have to estimate the head pose. On the other hand, tracking the face is also essential. Otherwise, extraction representative face samples are senseless. This thesis contains three main parts. First, once a face has been detected in a sequence, we try to extract the positions and sizes of the eyes, the nose and the mouth. Our approach is based on local energy maps mainly with a horizontal direction. In the second part, we estimate the head pose using the relative positions and sizes of the salient elements detected in the first part. A 3D face has 3 degrees of freedom: the roll, the yaw and the pitch. The roll is estimated by the maximization of a global energy function computed on the whole face. Since this roll corresponds to the rotation which is parallel to the image plan, it is possible to correct it to have a null roll value face, contrary to other rotations. In the last part, we propose a face tracking algorithm based on the tracking of the region containing both eyes. This tracking is based on the maximization of a similarity measure between two consecutive frames. Therefore, we are able to estimate the pose of the face present in a video frame, then we are also able to link all the faces of the same person in a video sequence. Finally, we can extract several samples of this face in order to apply a face recognition algorithm on them.
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Nam Jun Pyun. Extraction of an image in order to apply face recognition methods. Artificial Intelligence [cs.AI]. Université Sorbonne Paris Cité, 2015. English. ⟨NNT : 2015USPCB132⟩. ⟨tel-01578110⟩

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