Deep Learning based Real-time Object Recognition and Tracking for Immersive Training and Maintenance Applications

The immersive software market, which includes virtual, augmented and mixed reality, is expected to see tremendous global growth over the next five years as players from all sectors race to identify and capture market opportunities of the technology.
This project investigates into the business and technical aspects of immersive training and maintenance applications by taking various case studies. The initial of the project will investigate into the learning implications of immersive training and marketing, analyze available market opportunities and competition as well as develop a positioning strategy for the partner organization. A major part of the project would focus on the design and development of a comprehensive deep learning system for robustly detecting, superimposing and tracking 3D objects in digitally augmented applications under challenging environmental settings. The proposed MITACS Accelerate project will support the partner organization’s strategic plans to become a worldwide market leader in immersive VR/AR/MR training and maintenance solutions for manufacturing and automotive industries.

Faculty Supervisor:

Jiju Poovvancheri

Student:

Nursultan Sulaimanov;Sumesh Thakur;Vivek Kamra

Partner:

Modest Tree

Discipline:

Computer science

Sector:

Information and cultural industries

University:

Saint Mary's University