A facial recognition system is a technology capable of identifying or verifying a person from a digital image or a video frame from a video source. There are multiple methods in which facial recognition systems work, but in general, they work by comparing selected facial features from a given image with faces within a database. (Wiki)
These Facial Recognition Systems are famous as Artificial Intelligence Based Facial Recognition Systems. Artificial Intelligence Technology is receiving some of the biggest Technology-related bets. These investments are not just confined at organizations level but also at the National level where countries are betting on their economic growth and their GDPs with break-through AI technologies. Organizations have been scrutinizing and investing in Artificial Intelligence Start-ups and AI-powered technologies like Predictive Analytics, Visual Analytics, Recommendation engines, Customer Profiling, Security, Defense & Surveillance solutions, Facial recognition Solution and the list goes on.
Trying to achieve a clear return on investment has always been a goal. But it is debatable how much these organizations have been able to inculcate these technologies into their business and operational process for their long term growth and competitive advantage. Among these AI bets, it can be concluded with a fair amount of confidence that Facial Recognition is playing a key role in giving these organizations a finite Return on Investment.
Here are few organizations who are reaping the fruits of their AI investment:
- Time & Attendance Solution for Organizations Providing On-field Services via Mobile Apps: Existing ERP solutions, Workforce Management software are integrating Facial authentication features into their mobile App and Dashboard to replace username/password-based system which is cumbersome and bears security risk. Instead, they are bringing on-the-field Geo-tagged facial biometric attendance for field visits. AI-powered Face Recognition Start-ups in India and the Globe has given a clear competitive advantage to these Time and Attendance software companies by increasing their revenue and market share.
- Fintech organizations preferring to authenticate their users using Facial Recognition: Giving username and password with complex special characters accompanied by quirky small and capital letter combinations is how existing ERP systems expect users to sign up & log in. Ironically, by providing such complex string Insurance and Bank employees/users over-estimate the safety and security around these passwords. Adding to the pain is when users get auto-logged out and then needing to log-in again on an average 12-13 times in a day. This pattern seems to be common in Insurance and banking space, and it becomes extremely cumbersome, inconvenient and time consuming for employees to access their own digital workplace. Lastly, exchanging and sharing of usernames and passwords among users is an open secret. Extreme vulnerabilities always cloud around these credentials as they are shared and logging to the systems by proxies is a prevalent practice. Face Recognition API integrated into the log-In pages of these ERP systems has bailed out many such Insurance and banking companies platforms from possible security breaches. Using facial features and real-time authentication users can seamlessly log-in just like unlocking the phone using fingerprint. The AI technology not only smoothly logs-in the employees without having to remember those complex passwords, but it also ensures that only authorized users are getting logged-in, eradicating all possibilities of exchanging usernames and passwords and hence avoiding proxy.
- FMCG Organizations providing on-field operational delivery and services/On-field Sales driven companies using Facial Recognition for authentication: Millions of fingerprint devices are omnipresent in offices for daily check-in and check-out attendance. When it comes to one-field based attendance, there is a huge gap to track employees’ attendance and that affects productivity. Since FMCG and other On-Field sales-dependent companies solely rely on their sales & services officers to make daily visits to stores for engagement with retailers, marketing and logistics, it becomes crucial for an organization to measure the employee on-field productivity. An existing workforce management App integrated with Face Recognition APIs allows users to take their selfies which is Time tagged and Geo-tagged. This seamlessly mark their biometric attendance on their daily prospecting and sales visits.
Other Prevalent Artificial Intelligence return on Investments where countries and organizations are able to see fruitful results are listed below:
- City traffic video analytics
- Tunnels traffic video analytics
- Bridge traffic video analytics
- Highways traffic video analytics
- Pedestrian People counting
- Demographics (Age/Gender estimation)
- Identifying various Traffic Violations
- Red light Violations
- Triple ridding
- Ridding without helmets
- Wrong-way Driving
- Traffic Congestions
- Over speed detection and flagging
- Suspicious Incidences (Object Detection)
- Illegal Parking
- Yellow Box Violations
- Black List Alarm (Terrorists, Known Offenders, etc.)
- VIP Identification
- Forensic Analysis
- Demographic Profiling (Age Group and Gender Detection)
Global Facial Authentication Systems Market size (Source) is projected to grow at a CAGR of 13.0% during 2019–25 and it would be a minimum of $ 7.3Billion market. The facial recognition market is divided on the basis of technology, component, and application. The technology segment includes 2D, 3D, and facial analytics. Among the three, the 3D facial recognition technology segment holds a significant share in the world facial recognition market owing to its high accuracy in terms of recognizing facial features as compared to 2D facial recognition. The component segment is bifurcated into hardware (scanners, cameras, handheld devices, integrated devices) and software. The application segment includes homeland security, a criminal investigation, ID management, physical security, intelligent signage, web application, business intelligence, photo indexing & sorting, and others (VIP recognition, automotive and phone, PC & banking login).
About Aindra Labs
The Facial Verification platform, powered by our CV (Computer-Vision) and ML (Machine-Learning) technology, is a robust engine to process Facial images captured by any low-cost photo-capturing device like a smartphone, IP camera, etc to authenticate a user based on his/her facial attributes. It is basically an identity verification SaaS product that offers verification services to global businesses.
Aindra Labs Facial Verification engine leverages its 7 years domain expertise in Computer Vision specific to facial recognition, its Intellectual Properties (IPs) and related technologies to provide facial-biometric authentication using selfie images and deter attempts of identity spoofing. Real-time verification results make it an ideal solution to recognize a person or a user for online business and on-field operations. Aindra Labs providers reliable API for face comparison which can be tried for free.