MIT scientists have developed a new set of software algorithms, a process they refer to as “Eulerian Video Magnification,” which applies spatial decomposition and temporal filtering to deconstruct visual elements of video frames and rebuild them in order to detect hidden information.
“These aspects could include the variations in redness in a man’s face caused by his pulse,” notes Technology Review. The process “can amplify aspects of a video and reveal what is normally undetectable to human eyesight, making it possible to, for example, measure someone’s pulse by shooting a video of him and capturing the way blood is flowing across his face.”
“Just like optics has enabled [someone] to see things normally too small, computation can enable people to see things not visible to the naked eye,” says MIT computer scientist Fredo Durand, a co-author of the research paper.
The team plans to release the software code this summer, and “predicts the primary application will be for remote medical diagnostics, but it could be used to detect any small motion, so that it might let, for example, structural engineers measure the way wind makes a building sway or deform slightly,” notes the article.
The technique works for any type of video footage. However, artifacts such as graininess will also be amplified, so higher quality video will have better results.
ETCentric staffer Phil Lelyveld asks: “Could this be used for video compression algorithm testing and evaluation?”
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