Understanding complex visual scenes is one of the hallmark tasks of computer vision. Given a picture or a video, the goal of scene understanding is to build a representation of the content of a picture (ie what are the objects inside the picture; how are they related; if there are people in the picture, what actions are they performing; what is the place depicted in the picture; etc.). With the appearance of large scale databases like ImageNet and Places, and the recent success of machine learning techniques such as Deep Neural Networks, scene understanding has experienced a great deal of progress. This progress has made it possible to build vision systems capable of addressing some of the above-mentioned tasks. This line of research is being undertaken in collaboration with the computer vision group at the Massachusetts Institute of Technology. Our goal is to improve existing algorithms for scene understanding and to define new problems made attainable by recent advances in neural networks and machine learning.
Recognition of facial expressions
Facial expressions are a very important source of information for the development of new technologies. As humans we use our faces to communicate our emotions, and psychologists have studied emotions in faces since the publication of Charles Darwin's early works. One of the most successful emotion models is the Facial Action Coding System (FACS) 2, where a particular set of action units (facial muscle movements) act as the building blocks for six basic emotions (happiness, surprise, fear, anger, disgust and sadness). The automatic understanding of this universal language (very similar in almost all cultures) is one of the most important research areas in computer vision. It has applications in many fields, such as design of intelligent user interfaces, human-computer interaction, diagnosis of disorders and even in the field of reactive publicity. In this line of research we propose to design and apply state-of-the-art supervised algorithms to detect and classify emotions and ac...