Image Search by Image Similarity by Google

Congratulations to the Computer Vision Team at Google Labs! Google finally releases image search based on image similarities. 

Let’s review the different stages of image search:


1. Image-search-by-text-context: The first stage of image search is purely text based. The images with the same keywords in the context are extracted. This is still the most popular approach by almost all big image search players, such as Yahoo, Microsoft and Google. The advantages and disadvantages of image search by text context were discussed in a previous article.

2. Image-search-by-image-content: The content of an image is explicitly indexed by color, shape, texture, style, objects, etc., as described in our previous posts, Visual Search Engines: The Future Search Engines and Google and Microsoft Image Search by Content. One successful application of image search by image content is

3. Image-search-by-image-similarity: Image search by image similarity is basically image matching across different scale, illumination conditions, viewpoint changes or object occlusion. Some scale-invariant or affine-invariant features could be used to index images. Google similar image search uses text context to find overcomplete images, and then each image is associated with similar images. Tineye allows users to search similar images based on image examples. 

What is the next for image search? Will similar technologies be used for video search? Your comments are welcome.

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