Identifying Perceived Emotions from People's Walking Style

The GAMMA group has recently developed a new deep learning model that can identify people’s emotions based on their walking styles. The approach works by extracting an individual’s gait from an RGB video of him/her walking, then analyzing it and classifying it as one of four emotions: happy, sad, angry or neutral.

“Emotions play a significant role in our lives, defining our experiences, and shaping how we view the world and interact with other humans,” Tanmay Randhavane, one of the primary researchers in this project and a graduate student at UNC, told TechXplore. “Perceiving the emotions of other people helps us understand their behavior and decide our actions toward them. For example, people communicate very differently with someone they perceive to be angry and hostile than they do with someone they perceive to be calm and contented.”

Read all about it here.