Estimating the target of interaction for each human in office space with obstacles using 3D observation

Conventional studies on human behavior recognition have mainly focused on individual actions, including facial expressions and postures. However, most human behavior involves face-to-face interactions with other humans or objects, such as PCs. The previous work on recognizing face-to-face interaction focused on recognition of each group of humans engaged in conversation in an open space, which is considered a free space without obstacles. However, face-to-face conversation in our daily activities also occurs in a space such as an office with various obstacles, which could interfere with the interaction. To cope with this interference, the arrangement of obstacles and humans in the space should be considered. Moreover, in an office space, humans interact not only with other humans but also with certain interactive objects, such as PCs. This study aims to detect the target of interaction of each person in a space with obstacles by considering the 3D positions and orientations of humans, interactive objects, and other obstacles. The 3D arrangement of humans and obstacles is obtained by observing the space with an RGB-D camera.