X

The browser version you are using is not recommended for this site.
Please consider upgrading to the latest version of your browser by clicking one of the following links.

  • Firefox
  • Safari
  • Chrome
  • IE
Minimum 3 character are required for search result
Minimum 3 character are required for search result

Sign In

Your username is missing
Your password is missing

By signing in, you agree to our Terms of Service.

Remember me

Forgot your username or password?

Don’t have an account? Sign up here for an account.

Intel® AI Builders - Social Hub

Get the DL on AI.

Social Hub

Blog List / Track Athletes in 3D Like Never Before, with Wrnch and Intel® DL Boost
10 Jan 2019

Track Athletes in 3D Like Never Before, with Wrnch and Intel® DL Boost

By Dr. Paul Kruszewski, Chief Executive Officer, wrnch

wrnch developed real-time 3D tracking using a computer vision and deep learning solution Across the world, sports are one of the strongest threads that bring people together. Over the years, innovations in technology have shifted how we play and experience games. Viewers at home increasingly look for new ways to understand how exactly a spectacular feat was accomplished just moments after they witness it.

After years of development, my team at wrnch has developed real-time 3D tracking using a computer vision and deep learning solution that can be deployed with any standard camera. This allows tracking of the motion and poses of athletes without them needing to wear any special suits and sensors.

Credit: Walden Kirsch/Intel Corporation

Additionally with our solution utilizing 23 skeletal tracking points, a number of advanced metrics, such as velocity, stride length, and speed, can be reported live. Not only does this revolutionize the viewing experience on television, but also allows for athletes and coaches to gain access to performance-altering data like never before.

As an Intel® AI Builders member, we tested our 3D tracking solution, which we earlier thought was feasible  only with GPUs, on Intel-powered CPUs and were blown away with the results. Using Future Generation Intel® Xeon® Scalable processors, codenamed Cascade Lake, to take advantage of the new Intel® DL Boost capability and Intel® Distribution of OpenVINO™ toolkit,we were able to improve inferencing speeds from 90 FPS to 450 FPS, a 5x increase*.

We’re thrilled with this improvement in performance and look forward to bringing this to market.

To learn more about wrnch and our solutions, visit https://wrnch.ai/, or follow us on Facebook  and Twitter.

https://newsroom.intel.com/news/2019-ces-intel-news-livestream-replay/#gs.SlSgtIcV
See wrnch at 33:06


*System #1 (The wrnch standard hardware spec) - Intel® Core™ i7 processor, NVIDIA GTX 1080 gpu, 128 GB of DDR4-2666, inference resolution 328x184, Caffe* machine learning framework; System #2 - Future Generation Intel® Xeon® Scalable processor, codenamed Cascade Lake, 128 GB of DDR4-2666, Inference Resolution 328x184, Intel® Optimization for Caffe*, Intel® Distribution of OpenVINO™ toolkit

Software and workloads used in performance tests may have been optimized for performance only on Intel microprocessors. Performance tests, such as SYSmark and MobileMark, are measured using specific computer systems, components, software, operations and functions. Any change to any of those factors may cause the results to vary. You should consult other information and performance tests to assist you in fully evaluating your contemplated purchases, including the performance of that product when combined with other products. For more information go to http://www.intel.com/performance/datacenter.

ai artificial-intelligence deep-learning computer-vision 3d-tracking sports athletes