Face-graph matching for classifying groups of people
Henry Shu, Andrew Gallagher, Huizhong Chen, Tsuhan Chen · 2013
When people gather for a group photo, they are together for a social reason. Past work has shown that these social relationships affect how people position themselves in a group photograph. We propose classifying the type of group photo based on the spatial arrangement and the predicted attributes of the faces in the image. We propose a matching algorithm for finding images from a training set that have both similar arrangement of faces and attribute correspondence. We formulate the problem as a bipartite matching problem where the faces from each of the pair of images are nodes in the graph. Our work demonstrates that face arrangement, when combined with attribute (age and gender) correspondence, is a useful cue in capturing an approximate social essence of the group of people, and lets us understand why the group of people gathered for the photo.