Abstract:
We present a project that proposes an algorithm which is able to segregate random
pictures into organized groups. We use the technique of unsupervised learning i.e.
clustering for doing so. Our effort makes it possible to cluster all images with respect
to the categories we create. Here we will focus on one ofthe categories i.e. poses.
We are using five datasets named Georgia Tech face database, Yale Face database,
CAS-PEAL, MIT-CBCL and Kohn Kanade. However, in this particular piece ofwork,
we will use Georgia Tech face database. We are focussing on mining the unlabelled
images having various poses into separate groups. For this we are applying the
unsupervised learning technique ofmachine learning. We are making clusters that will
gather similar poses ofthe subjects. Hierarchical Clustering method is being used for
this purpose. The images are inserted into the algorithm; they are then pre-processed
so that they all align over a specific set of resolution and image type. After preprocessing the algorithm.form clusters and sends images to their respective clusters.
