Fusion of face networks through the surveillance of public spaces to address sociological security recommendations

Researchers around the world are trying to address the ever increasing security requirements by bringing new approaches to surveillance specifically in public places like school, rail way, subway station, air port etc. To establish and sustain security in public spaces, surveillance plays a key role in technology-dependent governance common to many countries in the world. Traditionally, through the routine surveillance, an automated security system gains knowledge about people and their activities in a certain space. In this paper we are proposing a fusion algorithm to aggregate surveillance parameters from more than one such spaces. Inspired by existing works on social network analysis based on human photos, we propose a new face network structure model. These face network structures are later fused to obtain sociological parameters of a person of interest and gather recommendations about the circle of associates of that individual. We believe these type of recommendations are helpful in comprehensive investigation purposes.