The system also includes tools to help a user replace the sky in one image with the sky from another picture.
“Computer graphics has had enormous successes in the past decades, but it is still impossible for an average computer user to synthesize an arbitrary image or video to their liking,” says James Hays, who was not involved with the research and has a PhD in computer science from Carnegie Mellon University. He believes it’s important to develop more-sophisticated tools for inexperienced users. Such people could use a tool like SkyFinder to find an image they want or to make adjustments to an existing image. Hays believes SkyFinder’s main contribution is its user interface.
Ritendra Datta, an engineer at Google who has studied machine learning and image search, says that allowing computers to understand automatically what’s being shown in an image remains one of the major open problems in image search. “SkyFinder seems to be an interesting new approach” that works for one type of image. Datta believes that advances in specialized applications could eventually be applied on a broader scale.
He thinks, however, that thorough usability studies are badly needed for search systems that rely on automatic analysis of images.
Sun plans to improve SkyFinder by adjusting it to analyze more attributes of the sky and by expanding the database. For now, he says, systems that automatically analyze images have to be trained completely differently depending on what type of image they’re working with. However, he says his work with SkyFinder could be used to identify pictures of the sky among a general bank of images.