Name: Sparrow: Sport Analytics and Computer Vision Technology
Start: 2019-06-11T18:00:00-04:00
End: 2019-06-11T20:00:00-04:00
Location: The Jay Hurt Hub for Entrepreneurship and Innovation

Todd Eaglin from Sparrow will show us the challenges his team faced in applying computer vision to solve sports analytics problems.

Location: The Hub, Room 208

** Meetup Schedule **
• 6:00 - Networking
• 6:15 - Topic Presentation
• 7:15 – Chat with presenter
• 7:30 – Wrap Up.

Todd's Bio:

I received my PhD in Computer Science at UNCC. During my dissertation I did extensive work in computer vision, GPU and mobile computing, data analytics and visualization.

I’ve worked for many years as a software engineer and a data scientist at Lowes. I am now a co-founder and technology director at Sparrow.

I enjoy playing sports and being active. I played div II lacrosse at UNCC and I now do Crossfit. I also have a passion for flying airplanes. I hold a private pilots license and I fly regularly.

Abstract:

Bringing computer vision applications to the consumer market is a challenging process for businesses. In my presentation I detail the technological hurdles my company has overcome developing novel technologies for sports, physical therapy and health. I will also cover the scalability and economical challenges with bringing these technologies to mobile computing. Lastly, I will cover challenges we faced in acquiring data and areas of future work.

Outline of the talk:
-Introduction
•Who I am
•The team
•How I got here

-The company
•What we do
•What we’ve done

-Technology (Detail 1 example – Soccer kick)
•Problem statement + Challenge
-Analyze ~1500 frames in 5 seconds or less. (6 second video @ 240fps)
-Device limitations (Compute + Camera)
-Bandwidth/Network limitations-Lighting limitations
•Why Pose estimation is bad in production and at scale
•Edge computing + Machine learning + Cost
-Edge computing (Mobile) is challenging!
•How we overcame it (General tips).
•Closing thoughts.

-Generating data
•Challenge
•In some cases collecting data is unsafe.
•Data augmentation at scale
•GANs (Adversarial networks)
•Realtime raytracing and simulations
-Future work
•HMR (Human mesh recovery)

Chang

Machine Learning Group (Davidson, Lake Norman, Charlotte)

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Sparrow: Sport Analytics and Computer Vision Technology

The Jay Hurt Hub for Entrepreneurship and Innovation

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Machine Learning Group (Davidson, Lake Norman, Charlotte)

Sparrow: Sport Analytics and Computer Vision Technology

Machine Learning Group (Davidson, Lake Norman, Charlotte)

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