Abstrait

Automated Facial Expression Based On Human Emotion

Dr.A.Muthu kumaravel, P.Jennifer

The Concern treatment of individuals during interviews and interrogation have stimulated efforts to develop "non-intrusive" technologies for rapidly assessing the credibility of statements by individuals in a variety of observant environments. Methods or processes that have the potential to precisely focus analytical resources will advance operational excellence and improve analytical capabilities. Facial expressions have the capability to commune emotion and regulate interpersonal behavior. Over the past 30 years, scientists have developed human-observer based methods that can be used to classify and correlate facial expressions with human emotion. However, these methods have proven to be labor intensive, qualitative, and difficult to standardize. The Facial Action Coding System (FACS) is the most widely used and validated method for measuring and relating facial behaviors. The Automated Facial Expression Recognition System (AFERS) automates the manual practice of FACS, leveraging the research and technology behind the CMU Automated Facial Image Analysis System (AFA) system. This handy, near real-time system will detect the seven universal expressions of emotion (figure 1), providing investigators with indicators of the presence of deception during the interview process. In addition, the system will include features such as full video maintain, snapshot generation, and case management utilities, enabling users to re-evaluate interviews in detail at a later date