Face recognition is becoming the mainstream technology used in sectors starting from law enforcement to biometric security. In addition, many organizations started using it in light of the COVID-19 pandemic.
Facial recognition technology has a great potential to reduce physical contact or personal interactions and enforce COVID safety rules. Moreover, various IT giants offer cloud-based services like Microsoft Azure’s Face, Amazon Web Services Rekognition, etc.
Amazon’s Rekognition is a service that goes beyond face matching by detecting activities and understanding the movement. The ability to identify people and understand everything happening in a scene expands the technology’s use and business value.
Future of Face Recognition Technology
● Face Detection
Face detection technology performs the following essential tasks to obtain better performance of face-related applications:
- Determining facial regions in a picture against different backgrounds.
- Determining the face alignment, like size, position, and rotation.
With the development of various face-related applications, face detection technology has become important in recent years to detect faces under challenging situations.
● Face Alignment
Facial pose and expressions impact the accuracy of face recognition. Therefore, it is vital to align the shape and position of facial parts for accurate face recognition. So, it is necessary to have a robust
● Face Matching
Face matching technology extracts a vector feature from a face image to identify the pre-registration of the person in the photo. However, the conditions of registered and query images captured are not always the same.
Variations of illumination or posture and facial expressions constitute significant factors to match performance degradation. To solve this pose variation problem, you can use face normalization technology. It corrects the frontal face posture as well as the size and position of an image by using a 3D shape model.
Use Cases
The two critical applications for facial recognition technology are authentication and surveillance. Though both have a range of use cases, authentication has got acceptance by the public. It is convenient to outweigh the privacy implications.
The ease of unlocking Windows computers and smartphones with apps logging and authenticating transactions has made people comfortable with the technology. Meanwhile, it is also used in agreement with smart passports, speeding the immigration queues.
During COVID-19, most businesses apply facial recognition to build access management in the COVID-safe plan to return to work. It eliminates guest’s and staff’s requirement to check-in through communal touchscreen kiosks.
Face recognition technology can be integrated with self-service checkouts, supporting payments authorization or loyalty cards for completely touchfree transactions in the retail environment. In addition, various fraud detection applications in the financial sector are using this technology for two-factor authentication.
Also, some supermarkets are planning to encourage customers to ‘Just Walk Out’ with shopping bags by paying automatically. It is all thanks to artificial intelligence advances and facial recognition. The face recognition technology enables supermarkets to make completely checkout-less stores and minimal staff.
Conclusion
The future of face recognition technology is bright. It will indeed stay for a long time, so we should embrace its benefits. As seen above, various use cases show that facial recognition helps a lot. For example, it creates a safe environment, providing great security and enhancing customer experiences.
