AI Video Analysis in Athletics

An example of how AI pattern recognition can achieve fine grain pattern detection and matching.   Here in athletic training planning and evaluation.   Note links to an athletic tracking system that might be used to provide data to work with.    And simulate alternate situations.    An example of possible use in many domains.

NFL hopefuls are adding AI video analysis to their arsenal

Intel's 3D tracking could help guide athletes toward peak performance

By Chris Velazco  @chrisvelazco  in Engadget

More than 130 football players have been training under the watchful eye of the athletic performance development company EXOS in Arizona, all in hopes of landing a first-round NFL draft pick. As it turns out, though, the eyes they’ve been working in front of aren’t exclusively human. Intel today said that EXOS’s latest batch of NFL hopefuls have been training in front of video cameras that — with the help of the company’s 3D athlete tracking system — should give players and staff a finer sense of their “body mechanics or trouble spots.” ... ' 

Reconstructing Hidden Movement from Video

Depending on the quality of this, consider the implications in many areas.  We did lots in the area of video understanding, could have used this.  Below description and videos.

MIT CSAIL’s AI can reconstruct hidden movement from video footage alone  By Kyle Wiggers in Venturebeat

Seeing around corners and through walls is old hat for AI and machine learning algorithms, which are at the heart of systems (some of which use lasers) that produce images outside a sight line. But what about the much more challenging task of reconstructing hidden objects without special equipment?

Researchers at MIT’s Computer Science and Artificial Intelligence Laboratory say they’ve developed exactly that. Their system, which they lay out in a preprint paper published this week, can reconstruct hidden videos from the shadows and reflections on an observed pile of clutter. With nothing more than a video camera switched on in a room, it’s capable of “seeing” around corners even when those corners (and live-action performances) fall outside the camera’s field of view.  .... "

Video Understanding

Very good piece, with as you might expect, good demonstration video.   This takes such methods beyond captioning and close to what we continually do as humans, visually interpret and understand a contextually changing view.  A sort of visual scene understanding.   Sensory AI at its most useful.

Helping AI master video understanding  By Dan Gutfreund
Video Analytics Scientist, IBM Research AI

I am part of the team at the MIT IBM Watson AI Lab that is carrying out fundamental AI research to push the frontiers of core technologies that will advance the state-of-the-art in AI video comprehension. This is just one example of joint research we’re pursuing together to produce innovations in AI technology that solve real business challenges.

Great progress has been made and I am excited to share that we are releasing the Moments in Time Dataset, a large-scale dataset of one million three-second annotated video clips for action recognition to accelerate the development of technologies and models that enable automatic video understanding for AI.

A lot can happen in a moment of time: a girl kicking a ball, behind her on the path a woman walks her dog, on a park bench nearby a man is reading a book and high above a bird flies in the sky. Humans constantly absorb such moments through their senses and process them swiftly and effortlessly. When asked to describe such a moment, a person can quickly identify objects (girl, ball, bird, book), the scene (park) and the actions that are taking place (kicking, walking, reading, flying). ... "