SELF-MONITORING SYSTEM FOR VISION BASED APPLICATION USING MACHINE LEARNING ALGORITHMS
Automatic face detection is a complex problem which is concerned with the automatic identification of an individual in a digital image. There are many algorithms through which this process can be carried out. However, there are no solutions to detect faces automatically with low resolutions in various application scenarios. We can implement this project's computer vision system to predict whether the screens are near their vision or not. Monitors placed too close or too far away may cause problems that may lead to eyestrain. Viewing distances that are too long can cause you to lean forward and strain to see small text. This can tire the eyes and place stress on the torso because the backrest no longer provides that support. Viewing distances that are too short may cause eyes to work harder to focus (convergence problems) and may require sitting in awkward postures. For instance, the user may tilt their head backwards or push the chair away from the screen, causing you to type with outstretched arms. But there is no alert system for measuring distance automatically from monitor to eye. So in this project, we can design implementation for automatic alerts based on distance based on face recognition. The minimum distance is 0.38 m (l.2fi.) and the maximum distance is 1.02 m (3.3fi.). it can be achieved by using artificial intelligence. We can use a web camera to capture human head positions and separate the background from foreground head positions. Then using image processing techniques to detect face and recognize. Finally, calculate the distance from the monitor to the face via web camera. If the distance is minimum to the pre-defined threshold value means, an alert is automatically generated and intimate to users without using any sensors. And also extends the approach to design the parent-child framework to send alerts at the time of seeing unwanted websites.
Artificial Intelligence, Deep Learning, Distance Monitoring, Face Detection, Vision System.