Human Pose Estimation and Activity Monitoring in Hospital with Self-calibrating Cameras

The interns will work on improvements to algorithms using geometry and deep learning for estimating human pose of individuals and the distance between them. This is a difficult task to do from videos as it involves 1) the detection and 2) 3D metric reconstruction of persons in all kinds of poses and apparel. The interns will obtain hands-on experience in algorithmic development, programming, and running validation studies at UBC and HPC’s facilities.
The expected benefit to the partner organization are far-reaching. This work is laying the groundwork for Providence to establish a computer-vision based smart hospital where non-contact based detection models can benefit patient care in areas including but not limited to infection control and patient monitoring.

Faculty Supervisor:

Helge Rhodin

Student:

Partner:

Providence Health Care

Discipline:

Computer science

Sector:

Health and Related Sciences & Technology; Professional, scientific and technical services

University:

The University of British Columbia

Program: