A Statistical Approach to Automatically Detect How Many Persons Appear in a Video
Year: 2014
Authors: Cazzato D., Leo M., Distante C.
Autors Affiliation: University of Salento , Italy
National Resarch Council of Italy Institute of Optics, Italy
National Research Council of Italy Institute of Optics, Italy
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 statistical approach to address this challenging issue is presented: the number of persons that are present in a generic video (even having low resolution and/or taken from a mobile camera) is automatically detected and also the intervals of frames in which each person appears are extracted. 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.
Journal/Review: JOURNAL OF THE OPTICAL SOCIETY OF AMERICA B-OPTICAL PHYSICS
Volume: 1 (1) Pages from: 11 to: 23
KeyWords: video indexingImpactFactor: 1.451
