Grammar-like algorithm identifies actions in video

Photo courtesy of http://www.freeimages.co.uk/
Photo courtesy of http://www.freeimages.co.uk/

Body language is a powerful thing, allowing us to gauge the tone and intention of a person, often without accompanying words. But is this a skill that is unique to humans, or are computers also capable of being intuitive?

To date, picking up on the subtext of a person’s movements is still not something machines can do, however, researchers at MIT and UC Irvine┬áhave developed an algorithm that can observe small actions in videos and string them together, piecing together an idea of what is occurring. Much like grammar helps create and connect ideas into complete thoughts, the algorithm is capable of not only analyzing what actions are taking place, but guessing what movements will come next.

There are a handful of ways that this technology would benefit humans. For example, if could help an athlete practicing his or her form and technique. Researchers also posit that it could be useful in a future where humans and robots are sharing the same workspace and doing similar tasks.

But with any technological advancement comes the question of cost–not money, but privacy. In this case, would the positives outweigh the negatives? In what ways can you envision this tool being helpful for your everyday tasks?

 

 

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Computer Vision aids endangered species conservation efforts

Photo by Dr. Paddy Ryan/The National Heritage Collection
Photo by Dr. Paddy Ryan/The National Heritage Collection

In an effort to help protect and conserve endangered species, scientists have been tracking and tagging them for years. However, there are some species that are either too large in population or too sensitive to tagging, and researchers have been working on another way to track them.

Now, thanks to SLOOP, a new computer vision software program from MIT, identifying animals has never been easier. A human sorting through 10,000 images would likely take years to properly identify animals, but this computer program cuts down the manpower and does things much quicker. Through the use of pattern-recognition algorithms, the program is able to match up stripes and spots on an animal and return 20 images that are likely matches, giving researchers a much smaller and more accurate pool to work with. Then the researchers turn to crowdsourcing, and with the aid of adept pattern-matchers, are able to narrow things down even more, resulting in 97% accuracy. This will allow researchers to spend more practical time in the field working on conversation efforts instead of wasting time in front of a computer screen.

Computer Vision detects heart rate

Researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) are now using computer vision to determine heart rate. Using an algorithm that analyzes small movements in the head, researchers are able to connect those movements to the rush of blood caused by the beating heart, in turn determining the heart rate. This opens doors for testing those who, for one reason or another, maybe not be the best candidates for EKG testing.