Facial recognition technologies are software-based applications that use biometrics of the human face (such as the distance between the eyes, nose width, the shape of the cheekbones) to determine a person’s identity. Typically, facial recognition software gathers these metrics from photographs or recorded or live video and compares them against a database of images of faces to find a match, meaning a face with identical biometrics. In this comparison and matching process, facial features picked out by algorithms are converted into a mathematical formula.
Facial recognition technology has been a surveillance tool since the 1990s, used by the US in criminal law enforcement and border control. Now, it is actively being expanded into the commercial sector for use in banks, retail stores, airlines, and restaurants, among other areas.
Facial recognition has potential to help enforce quarantine and social distancing rules
Demand for contactless biometric verification has spiked
The commercial adoption by retail, hospitality, and airline industries may slow down, given that these sectors have been hit badly by Covid-19
Facial recognition vendors have faced an added challenge to meet demand for verification on masked faces
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.
Disruptors in the facial recognition market focus mainly on offering products for access control, video surveillance, customer analytics, and payment gateways. Major industries using the technology apart from law enforcement and border control are retail, hospitality, gambling (casinos), and banking. Most software on offer can be used with existing camera and access control infrastructure.
Oosto (formerly known as AnyVision) provides a facial recognition-based platform named “Access Point AI” with touchless access control, video surveillance, occupancy analytics, people counting, and flagging dangerous behavior. The Israeli platform claims to be capable of spoof detection and liveness verification as well as integration with other cameras. The company has formed strategic partnerships with related technology providers such as Honeywell, Schneider Electric, Boon Edam, Ambarella, and Nvidia as well as several regional system integrations to grow its market reach. In October 2021, Oosto also partnered with Carnegie Mellon University’s (CMU) CyLab Biometric Research Center to focus on research and development in object, body, and behavior recognition, for commercial use. The company serves organizations across financial services, education, entertainment, healthcare, manufacturing, and distribution. In November 2021, the company introduced several new features to improve restricted zone alerting, recognition of masked individuals and forensics capabilities.
In March 2020, Microsoft, which invested in the company in June 2019, divested its stake due to ethical concerns over facial recognition technology. The company experienced reduced sales in 2020 owing to the Covid-19 pandemic which resulted in laying off around 50% of its staff along with cuts to research spending.
In July 2021, Oosto raised USD 235 million, bringing the company’s total funding to USD 352 million. The round was co-led by SoftBank’s Vision Fund 2 and Eldridge Industries with participation from existing investors including Robert Bosch GmbH, Qualcomm Ventures, and Lightspeed. The company expects to use the funding to improve its platform, accelerate the integration of its technology to edge computing devices such as smart cameras, bodycams, and chips, and expand into new markets.
Access Control and Verification:
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.
No investor data is available