Person Identification in Webcam Images: An Application of Semi-Supervised Learning

An application of semi-supervised learning is made to the problem of person identification in low quality webcam images. Using a set of images of ten people collected over a period of four months, the person identification task is posed as a graph-based semi-supervised learning problem, where only a few training images are labeled. The importance of domain knowledge in graph construction is discussed, and experiments are presented that clearly show the advantage of semi-supervised learning over standard supervised learning. The data used in the study is available to the research community to encourage further investigation of this problem.