20-06-2013, 03:09 PM
Face recognition
Face recognition.pptx (Size: 1.51 MB / Downloads: 15)
Introduction
Face recognition has become a popular area of research in computer vision and one of the most successful applications of image analysis and understanding.
A set of two task:
Face Identification: Given a face image that belongs to a person in a database, tell whose image it is.
Face Verification: Given a face image that might not belong to the database, verify whether it is from the person it is claimed to be in the database.
DIFFERENT APPROACHES
Different methods of face recognition.
Feature extraction methods
Holistic methods
Hybrid methods
Feature extraction methods
Feature extraction is the task where we locate facial features,
Eg: the eyes, the nose, and the chins etc.
This task may be performed after the face detection task Or recognition time.
big challenge for feature extraction methods is feature “restoration“.
Facial features are invisible according to the large variation.
This method is widely used to create individual vectors for each person in a system, the vectors are matched when an input image is being recognized.
Holistic methods
Holistic methods uses the whole face region as the input to a recognition system.
focuses a holistic method using eigenfaces to recognize still faces.
Hybrid methods
Hybrid face recognition systems uses a combination of both holistic and feature extraction methods.
Hybrid method of face recognition by using 3D morphable model. The model makes it possible to change the pose and the illumination on the face.
Problems of Face Recognition
when comparing a database image with an input image. The main concern is of course that all images of the same face are heterogeneous.
When image databases are created they contain good scenario images.
concerning deferent facial expressions as well. The system must be able to know that two images of the same person with deferent facial expressions actually is the same person.
CONCLUSION
Introduction of face Recognition
How facial recognition works.
Face detection and recognition.
Different approaches of face Recognition.
Feature extraction methods
Holistic methods
Hybrid methods
Problems
Face recognition.pptx (Size: 1.51 MB / Downloads: 15)
Introduction
Face recognition has become a popular area of research in computer vision and one of the most successful applications of image analysis and understanding.
A set of two task:
Face Identification: Given a face image that belongs to a person in a database, tell whose image it is.
Face Verification: Given a face image that might not belong to the database, verify whether it is from the person it is claimed to be in the database.
DIFFERENT APPROACHES
Different methods of face recognition.
Feature extraction methods
Holistic methods
Hybrid methods
Feature extraction methods
Feature extraction is the task where we locate facial features,
Eg: the eyes, the nose, and the chins etc.
This task may be performed after the face detection task Or recognition time.
big challenge for feature extraction methods is feature “restoration“.
Facial features are invisible according to the large variation.
This method is widely used to create individual vectors for each person in a system, the vectors are matched when an input image is being recognized.
Holistic methods
Holistic methods uses the whole face region as the input to a recognition system.
focuses a holistic method using eigenfaces to recognize still faces.
Hybrid methods
Hybrid face recognition systems uses a combination of both holistic and feature extraction methods.
Hybrid method of face recognition by using 3D morphable model. The model makes it possible to change the pose and the illumination on the face.
Problems of Face Recognition
when comparing a database image with an input image. The main concern is of course that all images of the same face are heterogeneous.
When image databases are created they contain good scenario images.
concerning deferent facial expressions as well. The system must be able to know that two images of the same person with deferent facial expressions actually is the same person.
CONCLUSION
Introduction of face Recognition
How facial recognition works.
Face detection and recognition.
Different approaches of face Recognition.
Feature extraction methods
Holistic methods
Hybrid methods
Problems