Machine learning methods for face keypoints location

• 1、School of automation, Beijing university of posts and telecommunications,Beijing 100876

Abstract：As an information carrier, human face has its incomparable advantages and important to researches in the field of bioinformation technology. And face key point location is the middle link in the process of face information analysis. Since the 1990s, machine learning has been developing continuously. The research on the location of the key points of human face has been carried out by the wind, and the research results have been more mature up to now. Human face has both rigid and flexible attributes, which makes the solutions of early face key point localization are to combine contour model and local features. However, with the development of deep learning and the arrival of Age of Big Data, the frameworks based on regression gradually have occupied the leading position. In recent years, face key point localization methods based on convolution neural network is gaining popularity. The development of machine learning can be seen from the changing of the methods of face key point localization.In this paper, different methods of face key point location based on machine learning are comprehensively studied, and the advantages and disadvantages of various frameworks are compared and analyzed theoretically. The models of traditional algorithms of ASM and AAM classes are well interpreted. The regression-based algorithm can achieve better positioning accuracy and speed.

Keywords： machinelearning facekeypointslocation CNN