Amscreen, Quividi team up to bring face detection to digital advertising
Amscreen, Europe’s largest digital media network owner, will incorporate Quividi’s face tracking technology across its portfolio of advertising-supported networks. According to the company, Amscreen’s network of digital screens has an audience of over 50 million weekly with more than 6000 screens.
The two companies will be working together over the next few months to implement this solution with the aim of delivering rich audience statistics to retailers. Following a trial period, data showed 94% of shoppers have been viewing on-screen content while in store.
“Amscreen is a leader in its field and a forward-thinking innovator. Their decision to standardize audience measurement on their networks with our face detection technology is a great move for the ecosystem: digital out-of-home and digital place-based media will continue to grow faster as advertisers gain better understanding of their true return on investment,” Olivier Duizabo, CEO at Quividi said. “We are delighted to be working with them to bring this technology into the mass market. With ‘Measured by Quividi’ tracking technology now present in their screens, they are able to offer a new level of measurement and trust, compared to some of the more traditional techniques used by others. ”
Based in Paris, Quividi has been using anonymous face detection since 2006, and has counted over 2 billion faces to date.
As we’ve reported in BIometricUpdate.com, face coding and face detection technologies are quickly finding their spot in retailers and marketers’ toolboxes.
Real-time systems such as the one created between Quividi and Amscreen are also gaining traction in the market. NEC has recently announced the North American launch of its facial recognition product aimed at retailers, called NeoFace. This service allows retailers to profile customers to estimate gender, age and frequency of shopping.
Almax, an Italian mannequin maker has also recently introduced the EyeSee, a mannequin that watches customers and uses facial recognition to log age, gender and race.