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Wednesday, August 5, 2015

Improving Photos

Erase Obstructions from Photos with a Click

Researchers at Google and MIT came up with an algorithm that could make taking pictures of obstructed scenes like taking a panoramic photo.

Rachel Metz | August 4, 2015


If your attempts at mimicking Ansel Adams with your smartphone camera have been foiled by things like reflective windows or chain-link fences, researchers at Google and MIT may have a solution: an algorithm that can separate the foreground from the background and delete the obnoxious obstruction.

Researchers at Google and MIT came up with an algorithm that can separate visual obstructions in the foreground, such as this chain-link fence, from what you want to photograph in the background. Source: http://www.technologyreview.com/news/539936/erase-obstructions-from-photos-with-a-click/
The algorithm works by detecting differences between the foreground and background within a sequence of photos you’d take while moving your smartphone slightly, kind of like you would while taking a panoramic picture.

<more at http://www.technologyreview.com/news/539936/erase-obstructions-from-photos-with-a-click/; related link: https://sites.google.com/site/obstructionfreephotography/ (A Computational Approach for Obstruction-Free Photography. Tianfan Xue, Michael Rubinstein, Ce Liu, William T. Freeman. [Abstract: We present a unified computational approach for taking photos through reflecting or occluding elements such as windows and fences. Rather than capturing a single image, we instruct the user to take a short image sequence while slightly moving the camera. Differences that often exist in the relative position of the background and the obstructing elements from the camera allow us to separate them based on their motions, and to recover the desired background scene as if the visual obstructions were not there. We show results on controlled experiments and many real and practical scenarios, including shooting through reflections, fences, and raindrop-covered windows.]>

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