MIT researchers have developed a model that recovers valuable data lost from images and video that have been “collapsed” into lower dimensions.
The model could be used to recreate video from motion-blurred images, or from new types of cameras that capture a person’s movement around corners but only as vague one-dimensional lines. While more testing is needed, the researchers think this approach could someday could be used to convert 2-D medical images into more informative—but more expensive—3D body scans, which could benefit medical imaging in poorer nations.
“In all these cases, the visual data has one dimension—in time or space—that’s completely lost,” says Guha Balakrishnan, a postdoc in the Computer Science and Artificial Intelligence Laboratory (CSAIL) and first author on a paper describing the model, which is being presented at next week’s International Conference on Computer Vision. “If we recover that lost dimension, it can have a lot of important applications.”
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