In this paper we have developed a system which is able to extract the facial landmarks like jaw, eyebrows, nose, eye and mouth from human face. This is generally done in order to use the extracted data for analysis of the emotions that is depicted in human face. We have used openCV and Dlib library to detect the facial landmarks. There are many feature extraction techniques like Geometry-based Technique, Template-based Technique, Appearance-based Technique, Colour-based Technique, etc[9]. The Pre-trained file that we used to detect the facial landmarks was trained with an Ensemble of Regression Trees. Using the shape predictor of Dlib we passed the file over the input image and the detection was estimated through pixel intensity. The extracted pixel values were stored using pickle C object in python. Any suitable neural network may be farther used to train a model, from the extracted data from dataset/datasets, which is able to analyse the different emotions on human face. Our aim is to proceed further and train a model with neural network for Expression Analysis with special concentration on children.

Digital Image Processing, Facial Landmark Detection, Face Detection, Computer Vision

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