Face Identification and Recognition

Face identification and recognition technology is very well known for identifying a person from a video clip or image. This is done using many ways like comparing facial features, using a neural network, or using eigenfaces.

What Is Facial Recognition Technology?

Facial recognition involves the use of algorithms to scan and match the contours of a person’s face. The algorithms are either feature-based or image-based. The programming is so advanced it can identify the subtlest of differences. Facial recognition tools are designed to determine matrices like jaw length, the width of the nose, eye socket depth, and chin shape. The details are then compared with representations already collected in a database.

A face authentication system based on principal component analysis and neural networks consists of three stages; pre-processing, principal component analysis, and recognition.

• In the pre-processing stage, normalization illumination, and head orientation are done.
• The principal component analysis is applied to find the aspects of the face which are important for identification. Eigenvectors and eigenfaces are calculated from the initial face image set. New faces are projected onto the space expanded by eigenfaces and represented by a weighted sum of the eigenfaces. These weights are used to identify the faces.
• In the third step, a Neural network is used to create the face database. Recognition and authentication of the face are done by using the weights generated by eigenfaces.

Eigenfaces is the name given to a set of eigenvectors. Eigenface provides an easy way for face recognition as its training process is completely automatic and easy to code. Eigenface adequately reduces statistical complexity in face image representation. Eigenfaces can handle large databases and once the eigenfaces of a database are calculated, face recognition can be achieved in real-time.

Some of the well-known software with face recognition ability include:

• iPhoto (Apple)
• Lightroom (Adobe)
• OpenCV (Open Source)
• Photos (Apple)
• Photoshop Elements (Adobe Systems)
• Picasa (Google)
• Picture Motion Browser (Sony)
• Windows Live Photo Gallery (Microsoft)
• FotoBounce (Applied Recognition Inc)
• DeepFace (Facebook)

Benefits of Facial Recognition Technology

Facial recognition has evolved from its nascent stage. It has improved to show extremely accurate results. Recent improvements in technology have enabled a broader implementation of facial recognition. More and more companies are benefitting from facial recognition tools. 

Facial recognition has many applications in a variety of fields such as security systems, videoconferencing and identification however face detection is not 100% accurate most of the time. We will talk about the drawbacks of Face identification and Recognition later in this post.

1. Ensure Better Security 

The world has progressed from security measures like multi-factor authentication and security questions. Technological advancements have paved the way for companies to incorporate latest security measures. Examples include fingerprint, eye and face scanners. Facial recognition tools are the new face of security. 

It offers great protection against cyber-attacks and information theft. Each employee has a unique faceprint that is stored in a database. Advanced algorithms run scans on the face and convert the result into mathematical language. The details are then compared with the information stored in the existing database. 

2. Improve Employee Productivity 

Smartphones are a great distraction and people spend hours on these “mini-computers”. But using smartphones during work can affect productivity. In fact, according to the World Economic Forum, about 36% of workers belonging to the millennial group as well as Gen X spend “two hours or more checking their smartphones for personal activities during the workday.” 

Using facial recognition can help address the said concern. Companies that use facial recognition tools are more likely to improve employee productivity. They are able to monitor the check-in and check-out time of employees in addition to curbing unauthorized breaks. Face recognition programs and software allow businesses to record time and flag employees who fail to deliver tasks on time. 

3. Ensure Data Privacy 

The importance of data privacy cannot be overstated in this digital age. Almost all business operations have gone digital. Records of companies and employees are stored in large databases. Facial recognition prevents unauthorized access to employee data. It also allows businesses to protect the different levels of clearance when it comes to HR and accounting records. 

Line managers can use facial recognition to access the time sheets of their subordinates. Individual employees, however, have to be provided with limited access to company information. They can use facial recognition tools to access job-specific information. 

4. Ensure Time Management 

There was a time when attendance records were limited to registers and other safe-keeping books. Habitual latecomers would ask their colleagues to fill in their attendance. Errors were a routine thing due to mismanagement and lack of proper time-tracking techniques. 

The advent of tools such as facial recognition and thumb impression changed the game. With facial recognition, chances of human error and inaccuracies are minimized. Furthermore, employees are no longer able to falsify their entry and exit times due to time-tracking programs. 

5. Access Information with Greater Ease 

Facial recognition is a convenient way to access information. It does not require any code or special key for verification. You don’t have to worry about the loss of external information because it doesn’t involve one. Get your face scanned and access your locker. It’s that simple. 

6. Improve Customer Experience 

Facial recognition is evolving to enable companies to pursue target advertising techniques with greater clarity. It is expected that facial recognition will be in the mainstream hotel market by 2025. Many hotel chains are already experimenting with targeted dining recommendations using facial recognition tools. 

Drawbacks with Face Detection and Recognition: 

Face detection and recognition have failed many times because of various reasons like changes in expressions, plastic surgery, the angle at which a picture is taken, etc. Also, as the person grows old the saved data has no value.
When Face recognition was used to prevent public crimes, it failed completely as people were using masks to cover their faces.

Conclusion:

Among the different biometric techniques, facial recognition may not be the most reliable and efficient as compared to iris scan and finger scanning as these systems can generate accurate results. Having said that, Facial recognition has been used worldwide in recent years mainly for security scans. Airports, stations, public places, and crime detection are the major areas where Face detection and recognition is used. We hope that modern approaches will increase the accuracy of Face recognition and authentication.