Nielsen and Oxford Researchers Accelerate AI-Powered Image Recognition of Products in Stores

New York, NY — Sept. 24, 2019 — Nielsen (NYSE: NLSN) and the University of Oxford today announced a two-year collaboration to advance the use of artificial intelligence (AI) to identify and classify consumer packaged goods (CPG) products on shelves in retail stores. Facilitated between Nielsen’s Image Recognition group and the Visual Geometry Group (VGG) at the University of Oxford, this partnership brings together the world’s largest pool of product reference data with industry-leading brainpower around AI technology to yield greater accuracy in product identification and discovery.

Through this partnership, Nielsen is working directly with University of Oxford Professors Andrew Zisserman and Andrea Vedaldi (Department of Engineering Science), world-renowned computer scientists and pioneers in image recognition and AI research. Zisserman, Vedaldi and their team of research scientists will work together with Nielsen to more precisely and quickly identify and classify in-store products based on product images captured through Nielsen’s eCollection solution. The Oxford researchers will focus on building and enhancing the eCollection algorithms with increasingly advanced deep learning capabilities, enabling a more automatic detection of store products, promotions and prices without the need for manual intervention.

In recent years, Nielsen has advanced its eCollection image recognition capabilities with computer vision and machine learning so that large amounts of data and thousands of products can be processed. With an extensive track record of innovation, the VGG Oxford researchers are tasked with further enhancing Nielsen’s eCollection capabilities, which is expected to improve accuracy while reducing costs with Nielsen’s product identification and classification.

“Across industries, artificial intelligence has been extremely successful in using the scale of big data to drive value—but the next step is activating the very small details—like correctly and automatically recognizing specific features on different products, even when those products have similar visual characteristics,” said Arun Ramaswamy, CTO, Nielsen Global Connect. “By partnering with one of the top AI-focused university programs in the world, we’re taking the next step in driving business value from the most advanced implementation of emerging technology. We are excited to continue on our future-focused path with the University of Oxford.”

“Nielsen is uniquely positioned, as no company in the world has the in-store product data and image assets that Nielsen has,” said Andrea Vedaldi, Associate Professor of Engineering Science, University of Oxford. “Our collaboration with Nielsen provides us with the breadth of data to leverage the power of deep learning and to drive new innovations in the area, as we continue to work toward advancing neural networks and image understanding.”

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