SBIR Phase I: Using Neuroscience to Optimize Video Thumbnail Selection

The innovation of this neuroscience project will be used to build a proprietary model of how the human brain generates preference from the perception of visual information. This model will serve as the basis for a web-based software product that can automatically select the most visually appealing frame from an online video to be used as the thumbnail representing the video. Using neuroscience to predict the visual appeal of a thumbnail allows for automated identification of more engaging thumbnails that will increase click-through rates and, as a result, video views. This is critically important for publishers because the thumbnail is the direct point of contact between publishers, advertisers, and users, meaning that billion dollar revenue streams pass through this tiny image. By introducing state-of-the-art neurotechnology to online video thumbnail selection, the proposed innovation offers a scientific way to increase clicks rates, video views, and, as a result, revenue streams. The broader/commercial impact of the proposed innovation stems from the generality of the core technology, which is predicting human preference for visual information using neuroscience. Once developed, this automated video thumbnail selection method will revolutionize online video, and can easily be extended to optimize image selection for any online media. For example, static online display advertisements such as banner ads, thumbnails for products on e-commerce websites, consumer package design, product design, User Interface (UX) Design for mobile devices, and application icons. Together these commercial sectors generate trillions of dollars in revenue every year, creating an exceptionally large market for the technology. Through Neon's technology, the way in which Internet users interact with and select visual information will be transformed.