Related projects
Discover more projects across a range of sectors and discipline — from AI to cleantech to social innovation.
Facial expression is a universal language to convey emotions and significantly affects social interactions. While psychologists have investigated facial expressions for decades, they have recently found their way into human-computer interactions and the gaming industry. A lot of research has been published on automatic detection of human emotions given either a single image or a series of images. In this project, we propose a new method for facial expression interpretation over a time series of images. We will first identify key facial expressions utilizing convolutional neural networks (CNN) and long short-term memory (LSTM) methods. Then, we will interpolate between these key facial expressions utilizing artificial intelligence while tracking head, eye, mouth, and eyelid. Finally, we will classify the emotions conveyed by the facial expressions over the entire time series of images. We expect to improve the state-of-the-art performance with this approach. Furthermore, we think that this approach would be more easily conveyed to the animation and gaming industries.
W. Robert J. Funnell
Majid Soleimani
SeekShift
Engineering - biomedical
Information and cultural industries
Accelerate
Discover more projects across a range of sectors and discipline — from AI to cleantech to social innovation.
Find the perfect opportunity to put your academic skills and knowledge into practice!
Find ProjectsThe strong support from governments across Canada, international partners, universities, colleges, companies, and community organizations has enabled Mitacs to focus on the core idea that talent and partnerships power innovation — and innovation creates a better future.