Facial recognition technology refers to the use of facial biometrics (e.g., the distance between the eyes, nose width, and cheekbone shape) to identify individuals. Facial recognition software gathers these unique metrics from photographs and recorded or live video—converted to digital data—to compare them against a database of facial images to find a match with identical biometrics.
Facial recognition technology has been used in the US in criminal law enforcement and border control as a surveillance tool since the 1990s. Now, it is actively expanding into the commercial sector for use in banks, retail stores, airlines, and restaurants, among other areas.
Facial recognition has gained widespread adoption across diverse sectors, with prominence in the financial and consumer staples sectors. This specifically includes the financial services for the financial sector, as well as the food products subsegment for consumer staples.
The adoption rates for security (physical access controls) have been relatively high, as facial recognition offers a relatively faster and accurate verification of individuals entering premises, including its ability to identify multiple persons simultaneously. The technology has also been used to improve customer experience (through remote customer onboarding), resulting in time and effort savings for both customers and businesses.
We have identified key additive manufacturing use cases below:
Incumbents in the field develop in-house technology for their own use to enhance their product offering, for example, Facebook and Google using facial recognition technology for automatic photo tagging in their tech platforms. Among the incumbents, Amazon and IBM also provide services to external customers.
Amazon and several disruptors have partnered with government agencies to provide facial recognition technology. The majority of the disruptors either 1) offer a ready-to-use facial recognition software/product, targeting the business-to-consumer (B2C) market or 2) offer the software targeting both B2C and business-to-business (B2B) markets through application programming interfaces (APIs) and software development kits (SDKs) that can be used by other developers to build facial recognition products.
Most incumbents use technology developed in-house for use in their own products. For example, Facebook and Google use facial recognition technology for automatic photo tagging. They have also acquired startups with complementary technology to strengthen their offering. Other incumbents, such as Amazon, Evolv Technologies, and Acuant, compete with startups in the market. For example, Amazon competes with startups via Amazon Rekognition, which has been used by US law enforcement until recently. Acuant also competes with many startups providing identity verification solutions.