Affectiva Announces New Emotion AI Attention Metric with Smart Eye’s Sophisticated Eye Tracking Technology

Today, Affectiva, a Smart Eye company, announced a new attention metric in its cloud-based Emotion AI offering. This metric, bolstered by Smart Eye's advanced automotive safety-grade eye tracking technology, represents a significant leap in viewer attention measurement for brands, advertisers, entertainment companies, and their market researchers. The unique and comprehensive measurement analyzes gaze and head position, delivering unparalleled accuracy and insights.

With a distinguished heritage in advertising measurement, Affectiva's Emotion AI technology is harnessed by over 90% of the world's largest advertisers. It empowers these industry leaders to delve into the minds of viewers, gauging emotional reactions and predicting engagement with their advertising and shows. By analyzing viewers' facial expressions, Affectiva's technology uncovers whether individuals respond as intended to the content. Now, as part of the Smart Eye company, this integration of Affectiva and Smart Eye's innovative technologies offers unparalleled insights into viewer behavior, addressing the pressing questions in the market research industry, such as whether viewers truly engage with the ad campaigns that businesses spend millions to produce and place.

For over 20 years Smart Eye, a pioneer of Human Insight AI, has provided industry-leading eye tracking technology to the automotive industry. It has played a pivotal role in measuring driver attention – understanding if drivers are looking on or off the road. Embedded in more than a million vehicles on the road worldwide, Smart Eye technology has dramatically improved road safety. Following its acquisition of Affectiva, the two companies combine their Emotion AI and eye tracking technologies to deliver a single solution that understands viewer attention when consuming brand, advertising and entertainment content.

Together, Smart Eye and Affectiva leverage their large and diverse datasets, including 10K hours of automotive data and 14.5 million face videos from 90 countries, to build highly accurate algorithms. The next iteration of this Emotion AI technology, featuring the upgraded attention metric, harmoniously combines the Affectiva facial expression technology with Smart Eye's best-of-breed eye tracking. This calibration-less metric seamlessly adapts to various cameras and devices, enabling clients to measure low attention signals like gazing away, speaking, and drowsiness. Moreover, it adeptly detects facial occlusion and visibility, enabling a comprehensive breakdown of viewer behavior for a deeper understanding of engagement.

"We're thrilled to announce this groundbreaking attention metric, driven by sophisticated eye tracking that unveils new dimensions of gaze and head position analysis,” said Graham Page, Global Managing Director of Affectiva Media Analytics at Smart Eye. “By merging Smart Eye's eye tracking prowess with our Emotion AI, we offer a remarkably precise and holistic viewer attention measurement that goes beyond traditional metrics This innovative approach not only provides insights into where viewers are looking but also delves into why they are looking there, capturing the full spectrum of viewer engagement, including emotional responses and cognitive processing. This comprehensive understanding of viewer attention enables advertisers and content creators to make more informed decisions and refine their strategies for maximum impact."

Affectiva's drive for an ads-focused, calibration-less attention measure is gaining rapid momentum. The company employs a comprehensive approach, leveraging its expertise in gaze measurement to estimate attention on ads. Initial findings highlight the significant potential of this innovative approach, especially when combined with complementary technologies such as in-context advertising exposure techniques.

The new attention metric marks a leap forward in comprehending viewer attention dynamics and is poised to make a profound impact on media effectiveness research.


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