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CV Case Study: Tracking Attentiveness & Emotion

With the influx of accessibility to image and video data, computer vision is taking off! Data science teams are now able to gain deeper insights through CV than ever before. However, labeling and annotating images can prove to be a more complex task than anticipated, especially when it comes to sentiment analysis. How do you efficiently and effectively label attentiveness on 1 million images? 
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Alegion’s robust CV capabilities were able to help a leading entertainment company accurately understand their TV audience engagement. Our platform was able to provide the insights needed to understand how many people were watching, their attention level and even their emotions, at scale and in real time. 
This case study shows how leveraging high-precision data annotation empowers companies to understand audience behavior. 
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