Face alignment is an important feature for most facial images
related algorithms such as expression analysis, face recognition or detection etc. Also, some images lose information due
to factors such as occlusion and lighting and it is important to
obtain those lost features. This paper proposes an innovative
method for automatic face alignment by utilizing deep learning. First, we use second order gaussian derivatives along
with RBF-SVM and Adaboost to classify a first layer of landmark points. Next, we use branching based cascaded regression to obtain a second layer of points which is further used
as input to a parallel and multi-scale CNN that gives us the
complete output. Results showed the algorithm gave excellent results in comparison to state-of-the-art algorithms
