Affiliations: [a] Recipient of a DOC-team-fellowship of the Austrian
Academy of Sciences at the Department of Social Studies of Science, University
of Vienna, Universitätsstraße 7/Stg. II/6. Stock, A-1010 Vienna,
Austria. Tel.: +43 1 4277 496 15; E-mail: christoph.musik@univie.ac.at
Abstract: An increase in video surveillance systems, paired with increased
inquiry for efficiency, leads to the need of systems which are able to process
and interpret video data automatically. These systems have been referred to as
'algorithmic video surveillance', 'smart CCTV', or 'second generation CCTV
surveillance'. This paper differentiates and focuses on 'high-level semantic
video surveillance' by referring to two case studies: Facial Expression
Recognition and Automated multi-camera event recognition for the prevention of
bank robberies. Once in operation these systems are obscure, therefore, the
construction process of high-level semantic VS is scrutinized on the basis of a
'technology in the making' approach.
Keywords: Algorithmic video surveillance, smart CCTV, technology in the making, facial expression recognition, event recognition, computer vision
