Facel expression recognition
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This document provides an overview of facial recognition systems. It discusses what facial recognition is, which is a computer system that identifies people by analyzing facial features from images and video. It explains that facial recognition started in the 1960s and is now commonly used for security applications. The document outlines different approaches to facial recognition, including two-dimensional and three-dimensional systems, and describes some of the techniques involved like feature extraction and classification. It also provides details about a specific facial recognition product called FA007 and its uses for access control.
Facel expression recognition
- 2. CONTENTS Facial expressions What is facial recognition system? Why to use? Two Dimensional Three Dimensional Approaches FA007
- 3. FACIAL EXPRESSIONs The seven universal expressions of emotion
- 4. WHAT is it? A facial recognition system is a computer application for automatically identifying or verifying a person from a digital image or a video frame from a video source. One of the ways to do this is by comparing selected facial features from the image and a facial database. Research on this technology started in the mid 1960s.
- 5. WHY TO USE? It is typically used in security systems and can be compared to other biometrics such as fingerprint or eye iris recognition systems.
- 6. Two-Dimensional Before the advent of faster computers and complicated imaging software, two- dimensional facial recognition systems were used. The problem that arose from this type of facial recognition system was the fact that the person to be identified must be facing the camera at no more than 35 degrees for accurate identification to be possible. Light differences and facial expressions also contributed to low accuracy in recognition of such systems.
- 8. Three Dimensional The new facial recognition systems make use of three-dimensional images and are thus more accurate than their predecessors. Just like two-dimensional facial recognition systems, these systems make use of distinct features in a human face and use them as nodes to create a face print of a person. Unlike two-dimensional face recognition systems, however, they have the ability to recognize a face even when it is turned 90 degrees away from the camera. Moreover, they are not affected by the differences in lighting and facial expressions of the subject.
- 9. APPROACHES Image Acquisition: Images used for facial expression recognition are static images or image sequences. An image sequence contains potentially more information than a still image Pre-Processing: Expression representation can be sensitive to translation, scaling, and rotation of the head in an imaged. Feature Extraction: Feature extraction converts pixel data into a higher-level representation- of shape, motion, color, texture of the face or its components. The extracted representation is used for subsequent expression categorization.
- 10. Classification: Expression categorization is performed by a classifier. The two main types of classes used in facial expression recognition are action units (AUs) and the prototypic facial expressions defined by Ekman. The 6 prototypic expressions relate to the emotional states of happiness, sadness, surprise, anger, fear, and disgust. Post-Processing: Post-processing aims to improve recognition accuracy, by exploiting domain knowledge to correct classification errors.
- 12. FA007 FA007 is an embedded facial recognition system, which applied for high level access control application. Its classic slope and industrial design is good for market like Government, Civil ID. It is also good for commercial market like Enterprise, Bank, building automation and so on.
- 13. THANKS