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.