1. FACE RECOGNITION

2. 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. Live face detection. B y comparing selected facial features from the image and a facial database.

4. Identify face features. Train the system with a convenient database. Face Detection Image processing Face recognition IMAGE INPUT Training Database

5. Extracting landmarks, features from an image of the subject's face. Analyze the relative position, size, shape of the eyes, nose, cheekbones, and jaw. G eometric, which looks at distinguishing features. P hotometric, that distill an image into values and comparing the values with templates to eliminate variances.

6. Principal Component Analysis. Linear Discriminate Analysis. Elastic Bunch Graph Matching Fisher Face. Hidden Markov Model.

7. Principal Component Analysis (PCA) is a known powerful technique under the broad title of factor analysis. Reduce the large dimensionality of the data space (observed variables) to the smaller intrinsic dimensionality of feature space (independent variables). P rediction, redundancy removal, feature extraction, data compression, etc.

8. Claimed to achieve previously unseen accuracies. Uses 3-D sensors to capture information about the shape of a face. T o identify distinctive features on the surface of a face, such as the contour of the eye sockets, nose, and chin.

10. It is not affected by changes in lighting like other techniques. It can also identify a face from a range of viewing angles, including a profile view. Even a perfect 3D matching technique could be sensitive to expressions.

11. Detect the face Enhance the image Identify nose and boundaries

12. ORL DATABASE A set of pictures taken between 1992 and 1994 at Olivetti Research Laboratory. Different times, expressions, lightning and details 10 images per person

13. Yale Face Database B 165 images of 15 individuals. There are 11 images per subject, one per different facial expression.

14. Recognize criminals. Simultaneous multiple face processing. In public spaces (airports, shopping centers). Verify identity to grant access in restricted areas. H older of the passport is the rightful owner or not.

15. ATM would capture an image of your face, and compare it to your photo in the bank database to confirm your identity. By using a webcam to capture a digital image of yourself, your face could replace your password as a means to login.

16. Pretty good at full frontal faces and 20 degrees off. Include poor lighting, sunglasses, long hair, other objects partially covering the subject’s face, and low resolution images. Another serious disadvantage is that many systems are less effective if facial expressions vary. Even a big smile can render in the system less effective.

17. Already in use mainly for security an human-machine interface applications. Facial recognition system identifies the particular person and grant the access.