Facial recognition system is a combination of hardware and software, which identifies and verifies a person by comparing and analyzing the facial patterns of a person using deep learning. Moreover, facial recognition system is mainly used in security purposes, and also have application in different areas such as payment, access control, and others. Face recognition system uses four different steps to analyze and identify the person, which includes face detection, face alignment, feature extraction, and finally face recognition.

Increasing demand for surveillance systems to improve public safety and security is expected to increase adoption of facial recognition systems

Face recognition system find major application in public security using surveillance cameras to track the criminals. Moreover, growing concern regarding security threats has resulted to install face recognition system in most of the public places such as airport, metro stations, open market, country borders, and other public places, which helps to keep track on the criminals. For instance, in October 2017, three units of Panasonic's facial recognition systems was installed at Tokyo International Airport's immigration control. These were installed to verify traveler’s identity by comparing travelers face using the IC chip embedded in the person's passport with the photo taken by face recognition system. Furthermore increasing adoption face recognition system by government bodies and defense authorities is expected to drive the market growth over the forecast period 2019-2027.

Increasing adoption of face recognition system in mobile devices for authentication and data security purpose is expected to drive the market growth over forecast period

Maintaining information security in mobile devices has become increasingly important, owing to which some of the major mobile companies such as Apple Inc, Samsung Electronics, and OnePlus are focused on implementing face recognition system in their latest devices to protect and secure their user’s data. For Instance, in September 2017, Apple Inc launched IPhone X, which uses 3D facial recognition to unlock the phone and is considered to be more secured compared to password unlock system. Moreover, increasing online payment transaction from mobile devices has also led the app developers to develop face recognition app to authenticate users identity before making the payment. These factors are expected to drive demand for face recognition system over the forecast period.

Furthermore, face recognition system market is expected to exhibit double digit CAGR, as this system is evolving at a faster rate and is expected to be used for almost all the security purpose in the near future, which is expected to drive the market growth over the forecast period. For instance, in August 2018, The Tokyo Organizing Committee of the Olympic and Paralympic Games (Tokyo 2020) announced to implement face recognition system at Olympic and Paralympic Games Tokyo 2020 to verify the identity of athletes, officials, other staff members, and media representatives for security and safety purpose. The Tokyo Organizing Committee in partnership with NEC Corporation will install these face recognition system.

Face Recognition System Market Taxonomy

On the basis of technology, the global face recognition system market is segmented into

2D Facial Recognition
3D Facial Recognition
Facial Analytics

On the basis of component, the global face recognition system market is segmented into

Hardware
Software

On the basis of application, the global face recognition system market is segmented into

Security and Law Enforcement
Payments
Access Control
Photo Indexing and Sorting
Emotion Recognition
Others (Robotics and eLearning)

On the basis of region, the global face recognition system market is segmented into

North America
Europe
Asia Pacific
Latin America
Middle East
Africa

Major players operating in the global face recognition system market include 3M, Animetrics, Aware, Inc., Ayonix Corporation, Cognitec Systems, Daon, Gemalto NV, Herta Security, IDEMIA, KeyLemon S.A., NEC Corporation, Neurotechnology, NVISO SA., Panasonic i-PRO Sensing Solutions Co., Ltd., and Techno Brain

About Author

Ankur Rai is a Research Consultant with over 5 years of experience in handling consulting and syndicated reports across diverse sectors. He manages consulting and market research projects centered on go-to-market strategy, opportunity analysis, competitive landscape, and market size estimation and forecasting. He also advises clients on identifying and targeting absolute opportunities to penetrate untapped markets.