At the end of 2019, as a Horizon CDT student in Nottingham University, I was attending a workshop (called Computer Vision for Physiological Measurement) in Seoul, South Korea. This workshop mainly focus on the research of applying recent advance in computer vision to measure the human physiological status.
This year, there are more than 50 people from company or academic institution attended this workshop and 19 of us were giving talks to share the research we did and discussing the potential future research directions.
During this workshop, I gave a talk about how to apply the state-of-the-art machine learning techniques to automatically detect emotions from people’s face. In particular, it utilised people's facial muscle movements to infer emotion status. This technique can be further applied to other purposes , as facial dynamics can reflect many different human status.
More importantly, how to apply such techniques to benefit our daily life was also discussed. For example, it can be further extended to make a quick and objective judgement about someone’s mental health, such as depression, or predict someone’s personality. Specifically, fast and automatically understanding human's personality is important in employment. It can help employers to better recognise which candidates are more suitable to the job, and more willing to work in a group. The mental healthcare is another potential application. For example, while it is expensive and time-consuming to find mental health experts to diagnose mental health, such technique can provide a cheap, quick and objective assesement to most patient as well as provide more useful information for related doctors.
In short, such techniques have great potential to improve the business and quality of our life. For investors, it could be a good direction to invest money and time.
Since this workshop was with ICCV conference, at the end of this event, I had a great time in the banquet, and had nice chats with other attenders.
