Facial Image Analysis: Recent Trends and Approaches

Abstract: In recent years face recognition has received substantial attention from both research com-munities and the market, but still remained very challenging in real applications. A lot of face recognition algorithms, along with their modifications, have been developed during the past decades. Deep learning has recently achieved very promising results in a wide range of areas such as computer vision, speech recognition and natural language processing. It aims to learn hierarchical representations of data by using deep architecture models. Facial emotion recognition is one of the most important cognitive functions that our brain performs quite efficiently. State of the art facial emotion recognition techniques are mostly performance driven and do not consider the cognitive relevance of the model. Similarly, Facial image analysis through 3D spectral information is gaining lot of scope. Hyperspectral cameras provide useful discriminants for human face recognition that cannot be obtained by other imaging methods. Hence, the facial analysis through Hyperspectral imaging is a great advantage. In this paper, we try to comprehend the recent emerging technologies in the field of image analysis for faces. Keywords: Face recognition, image analysis, 3D image, Deep Learning, Hyperspectral Imaging.