Authors:
Dario Cazzato
1
;
Marco Leo
2
and
Cosimo Distante
2
Affiliations:
1
University of Salento, Italy
;
2
National Research Council of Italy, Italy
Keyword(s):
Hartigan Index, Silhouette, Face Indexing, People Identification, Clustering.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Features Extraction
;
Image and Video Analysis
;
Segmentation and Grouping
Abstract:
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 method that, through different statistical indices, automatically
determines the number of people in the scene.