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Face Detection Systems are used for the identification of a person from digital images. The face detection system can extract the different facial features from a digital image. A set of facial features extracted from a digital image includes eyes, nose, mouth and face region. Face recognition is a difficult task due to the different facial expressions. With the help of a face detection system presence of a human face can be detected easily. For the detection of different facial features, the Viola-Jones algorithm is used in the proposed work. To make the task more manageable, Viola-Jones requires full view frontal upright faces.
This video is helpful for those who are working on Face Detection or Face Recognition Projects.
In this video, Different Facial Features like Eyes, Nose, and Mouth
are Detected from the Digital Images.
The algorithm used for Facial Features detection is: Viola-Jones
Algorithm.
Viola-Jones Algorithm is used for the Face Detection Projects for
Face Detection.
Viola-Jones Algorithm works on different parameters and
MATLAB Functions.
In this video, you can learn how to use the Viola-Jones Algorithm
for the Detection of Different Facial Features from the Digital
Images.
Facial FEATURES: In any recognition system, the selection of feature extraction plays a vital role. There are a lot of feature extraction techniques proposed efficiency of the proposed system is not acceptable due to the lack of appropriate feature selection.
Q.1. Which Algorithm is used for Face Detection?
Ans. Viola-Jones Algorithm
Q.2. Is this System can Detect any kind of Images?
Ans. Yes
Q.3. What types of Image Format can be Detected?
Ans. This Face Detection System Support all types of image
formats like jpg, png, tiff, jpeg, and bmp.
Q.4. Name the Image types supported by Face Detection system?
Ans. RGB images, grayscale mages, and Black and White images.
Q.5. Which MATLAB Version is used here?
Ans. MATLAB R2016a.
Q.6. Can you Send me Source Code?
Ans. No, I already Created Different Videos on Face Detection and
Source code is also present on the Screen. You can get help
from these videos.
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