Applying Deep Learning to Optimize 3D Pose Estimation from Monocular Video

REP is an athlete development platform for building better, and healthier athletes. Inside the REP platform are computer algorithms that can see how people move, and the accurately estimate how they are moving in three dimensions. The REP platform can then compare models of how you move, to models of how experts move. This comparison gives us rich information that people can use to improve their form. However, generating the expert models is quite hard, and its not always easy to understand how to actually compare users and experts. This MITACS project will allow us to work with a talented computer vision researcher to optimize our system through integrating our existing training datasets.

Faculty Supervisor:

Greg Mori

Student:

Jon Smith

Partner:

Athlyst Inc

Discipline:

Computer science

Sector:

Information and communications technologies

University:

Program: