Segmentation and detection of Human Face
Nizar Zaghden, Sirine Ammar, Mahmoud Néji · 2020
In this paper, we propose a system that classify Human faces, which are issued from video sequences captures. Segmentation of moving objects from video sequences plays an important role in many fields of computer science. We present some background subtraction approaches, then we compare their results. The DeepSphere" is employed in this paper to perform foreground objects detection and segmentation in video sequences. We employ the Deeplearning approach and the viola& Jones algorithms to segment faces from images. Finally, we classify the obtained faces using fractal dimensions.