A complete framework for fully-automatic people indexing in generic videos

Face indexing is a very popular research topic and it has been investigated over the last 10 years. It can be used for a wide range of applications such as automatic video content analysis, data mining, video annotation and labeling, etc. In this work a fully automated framework that can detect how many people are present in a generic video (even having low resolution and/or taken from a mobile camera) is presented. It also extracts the intervals of frames in which each person appears. The main contributions of the proposed work are that no initializations neither a priory knowledge about the scene contents are required. Moreover, this approach introduces a generalized version of the k-means