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An Advance In Image Recognition Software
Roland Piquepaille alerts us to work by US and Israeli researchers who have developed software that can identify the subject of an image characterized using only 256 to 1024 bits of data. The researchers said this "could lead to great advances in the automated identification of online images and, ultimately, provide a basis for computers to see like humans do." As an example, they've picked up about 13 million images from the Web and stored them in a searchable database of just 600 MB, making it possible to search for similar pictures through millions of images in less than a second on a typical PC. The lead researcher, MIT's Antonio Torralba, will be presenting the research next month at a conference on Computer Vision and Pattern Recognition.
This actually solves a problem I've been stumped on for a while. I need a way to search for similar images such that images that are similar have a searchable value with an inherent "nearness" quality.
That is, there are a number of image similarity algorithms, but the computed values of two similar images are not necessarily mathematically near to each other. This algorithm produces values that are, which can make searching for similar images among very many images, quite fast.
Yep, I second that. The article is really short on details. Not surprising since they're presenting it at a conference next month. We don't even know what kind of features they are extracting from the images. Are they using wavelets? Texture descriptors? Color information? Shape recognition? It sounds like a combination of true content based image recognition with keyword input association if I read the article correctly.
If they are claiming to have a general image recognition algorithm that'd be something. As it is a lot of research goes into recognizing specific kinds of things, such as faces, license plates, etc. I'm very curious to see what they've come up with.
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