Accurately Measuring Viewer Attention for Maximum Marketing Impact Using Computer Vision

Tuesday, May 21, 4:20 PM - 4:50 PM
Summit Track: 
Business Insights

Traditional techniques to measure television viewership have relied on active engagement from the audience in the form of button clicks and surveys. Not only do these techniques bias the captured data, they also fail to measure viewers’ attention levels as they cannot deduce whether viewers are actually in front of the TV, and if so, whether they are actually watching. This talk describes how TVision is leveraging the latest advances in deep learning and computer vision to measure viewer attention on a per-second basis and categorize attentive reach by demographic, time of day, channel and program.


Vinod Kulathumani

Lead Computer Vision Scientist, TVision Insights

Vinod Kulathumani is the Lead Computer Vision Scientist at Tvision Insights. His research interests are in the areas of embedded computer vision, machine learning and network-based sensing systems. He has published over 40 peer-reviewed conference and journal publications in leading venues, and holds one patent. Before joining TVision, he was an Associate Professor in the Department of Computer Science at West Virginia University. He has also co-founded Aspinity Inc., a start up focused on ultra-low-power sensing systems. He received his Ph.D. and M.S. degrees in computer science and engineering from the Ohio State University and his B.S. degree in computer engineering from the University of Mumbai.

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