OpenCV is a program with modules and scripts for advanced video techniques, including face detection using a webcam. The Haar Cascade module provides limited face detection capabilities, but programmers are working to improve it to recognize specific faces. The system uses common facial attributes to determine if a real face is displayed, but problems arise if facial coordinates are not where expected. The facial detection system has potential uses in security and image storage.
Open Source Computer Vision Library (OpenCV) is a program that includes many modules and scripts for advanced video techniques on a computer. One of the scripts is OpenCV’s face detection, which uses a webcam to detect faces. As of 2011, many programmers are working on a way to expand this module to recognize a particular face instead of simply recognizing if a face has been captured. This system works by recognizing common facial attributes, such as eyes and mouths, to determine if a real face is being displayed.
In the OpenCV program library, there is a script called Haar Cascade. This module provides a face detection system, but the detection has limited capabilities. OpenCV’s face detection, without modification, can only detect if a face is displayed. This is done by accessing the computer’s webcam and watching the video that returns. If common facial attributes such as eyes and mouth are detected, the OpenCV face detection system will say that a face is present.
New users of OpenCV may find it difficult to find the facial recognition script. Like many other scripts, this one is stored in the “Samples” section. By accessing the script, OpenCV can automatically use the recognizer system without the programmer having to manually install the script.
Many programmers are working on the OpenCV open-source interface to improve the OpenCV face detection system. Instead of simply recognizing if a face is being viewed by the webcam, the modified system would have to recognize specific faces. This is mostly done by taking an image of someone’s face, showing that person on the webcam, and then comparing the two images. If the images are similar, face detection will tell that the person is the same as the stored image.
Some problems are evident in the OpenCV face detection system, mainly with the effectiveness of the detection. These problems mainly arise from facial coordinates, such as the position of the eyes. If eyes or other facial elements are not where OpenCV expects them to be, it will say that a face is not present, even though it is. This requires programmers to manually enter the coordinates each time the facial interface is used.
OpenCV face detection has a few uses beyond just being fun, and it gives programmers a way to improve their skills. Facial detection can be used for security, especially when modified to recognize specific faces. This can also be used to easily store face images from a webcam, instead of accidentally capturing other images.
Protect your devices with Threat Protection by NordVPN
