This tie-up with EXOS may be the most noteworthy usage of Intels athlete tracking tech to date, but it wasnt always going to be that way. Viewers around the world were set to get a first-hand look during the 2020 Tokyo Olympics, where it wouldve overlaid algorithmically generation visuals of athletes kinds over replays of occasions like the 100-meter dash. The around the world COVID pandemic shuttered plans to stage the occasion last year, but such a high-profile tech demonstration might still be utilized when the Olympics begin later this year..
The beauty of Intels 3DAT system is that professional athletes dont need to strap on troublesome sensors, or stress over precarious positioning of equipment during drills. Instead, run-of-the-mill video footage is shuttled off to servers loading Intel Xeon Scalable processors packed with the businesss “Deep Learning Boost” AI acceleration capabilities. The system then tracks 22 unique points on a professional athletes body, and examines their form for speed, body angles, and velocity points. Those results are communicated back to training personnel in the type of chart-laden reports, all created to assist gamers better comprehend their running technique and ways it could be enhanced.
” This data allows us to make modifications in the weight room to help unlock more possible on the field,” stated Craig Friedman, SVP president of EXOS Performance Innovation Team, in a news release.
More than 130 football gamers have been training under the watchful eye of the athletic efficiency development company EXOS in Arizona, all in hopes of landing a first-round NFL draft choice. As it turns out, though, the eyes theyve been working in front of arent solely human. Intel today stated that EXOSs latest batch of NFL hopefuls have been training in front of camera that– with the assistance of the businesss 3D athlete tracking system– must provide gamers and staff a finer sense of their “body mechanics or problem spots.”
” 3DAT enables athletes to comprehend exactly what their body is doing while in movement, so they can specifically target where to make tweaks to get faster or better,” said Ashton Eaton, Intel item advancement engineer and two-time Olympic gold medalist.