The basic idea behind the Face detection is facial color de- tection. We all know that human skin consists of a wide range of colors. If by any means we could detect those ranges of col- ors, we can detect a face. This is the basic idea behind face de- tection. But as the range is too high we cannot put all the data just by coding. So we have to take certain idea from the field of Artificial Intelligence. We developed a Simple algorithm of learning. The idea was that we will choose some random faces and the computer will take their picture, detect the compo- nents of their skin color separately as RGB and stores those data in a table known as a Look up table. This look up table is maintained in a XML file and is incorporated into the code by use of a classifier.
After the face is detected by the color threshold, we draw a rectangle box around the detected face. (In our system, it is a
25,000 line long XML file (Look-up table). So; we ensured the accuracy as 92 %)This rectangle now becomes our Region of Interest (ROI). We store this ROI in a Database, so that later we can access the database to see the people who came to the room. At the same time the frames where we get the ROI is joined to form a High FPS Mpeg Video. As we will send the video over internet, so we recorded the video in high frame rate to decrease the video size. But in case of face images we used lossless format .bmp. So, the image size will be increased, but a lossless image format is always better for a future analy- sis. Though the space complexity will increase, but the time complexity will decrease. And in a security system, system speed is a notable issue. Detected faces and videos are shown in Fig. 2 and Fig. 3 respectively.
Then from the ROI the centre of the face is detected by the meeting point of the diagonals of the rectangle box. But this position is with respect to the ROI and not with respect to the original picture. So we have to again convert them with re- spect to the whole frame. After that the modified coordinate is written in a text file in a queue fashion.
HUMAN FACE DETECTION AND RECOGNITION - ethesis
OBOMANIAC Intelligent Tracking System is an intelli- gent system which can be used for security purposes. This project combines the joint venture to capture the frames
from a camera, detect the faces, saves the detected faces and tracks the faces.
This project has six distinct modules:
1. Face detection from the frame and creation of image
and video database.
2. Movement of camera as per movement of person.
3. Counter for how many persons are inside the room.
4. Natural Language Processing
5. Face Recognition System and
6. User interface
In this project we have used a Digital camera to acquire the
image. Then we detected the face from the image and stored
the face in a database for future use. The system tracks the face by the camera and it stores all the frames in a high FPS MPEG