Starry Night Mosaic Art

I'm posting here a picture that I generated using so called mosaic art, which is a technique used by several artists and designers consisting of depicting an image using smaller units of content. The smaller units can usually be other images, for instance, remember the poster of the movie The Truman Show? There is software available to generate this type of images, here is one named Mazaika. Mosaic art has also been popularized to some extent by artists such as Chuck Close or Juan Osborne's amazing text mosaics. I wanted to do a simple experiment that incorporates an additional variable that I haven't seen in previous mosaics.

Coming from a computer vision perspective my motivation here is that most mosaics that tile images try to match only the color of the image for each specific location but they do not capture other characteristics like gradients (a sense of directionality) which is a common feature in most of today's computer vision systems. Take as inspiration the picture of the Starry Night by Vincent Van Gogh, made available by the Google Art Project at incredible resolutions. I'm including here a pretty high res picture if you click on it but feel free to explore the link above.

Click on the image for higher resolution.

For this kind of image, gradients are just as beautiful as colors and a good mosaic should be capturing both when tiling images. I used a database of 1 million pictures taken from Flickr to retrieve the closest matching image regarding both color and gradients for every tile in the composition. I also made sure to add some randomization so that nearby tiles don't get too similar images and only slightly modified the tonality of the resulting picture. I will try to update this post if I find a way to return even better matches regarding color and gradients or better tiling but I hope this mosaic conveys the idea of using gradients (a popular cue for many state of the art feature descriptors in computer vision) for creating mosaics.

Click on the image for higher resolution