Camera Surveillance as a Measure of Counterterrorism?

Camera surveillance has recently gained prominence in policy proposals on combating terrorism. We evaluate this instrument of counterterrorism as resting on the premise of a deterrence effect. Based on comparative arguments and previous evidence on crime, we expect camera surveillance to have a relatively smaller deterrent effect on terrorism than on other forms of crime. In particular, we emphasize opportunities for substitution (i.e., displacement effects), the interaction with media attention aspired to by terrorists, the limits of real-time interventions, the crowding-out of social surveillance, the risk of misguided profiling, and politico-economic concerns regarding the misuse of the technology.Camera surveillance, closed-circuit television (CCTV), public security, deterrence, terrorism

Camera Surveillance as a Measure of Counterterrorism?

Camera surveillance has recently gained prominence in policy proposals on combating terrorism. We evaluate this instrument of counterterrorism as resting on the premise of a deterrence effect. Based on comparative arguments and previous evidence on crime, we expect camera surveillance to have a relatively smaller deterrent effect on terrorism than on other forms of crime. In particular, we emphasize opportunities for substitution (i.e., displacement effects), the interaction with media attention aspired to by terrorists, the limits of real-time interventions, the crowding-out of social surveillance, the risk of misguided profiling, and politico-economic concerns regarding the misuse of the technology.Camera surveillance, closed-circuit television (CCTV), public security, deterrence, terrorism.

Network Data Mining: Methods and techniques for discovering deep linkage between attributes

Abstract. Network Data Mining identifies emergent networks between myriads of individual data items and utilises special algorithms that aid visualisation of ‘emergent ’ patterns and trends in the linkage. It complements conventional data mining methods, which assume the independence between the attributes and the independence between the values of these attributes. These techniques typically flag, alert or alarm instances or events that could represent anomalous behaviour or irregularities because of a match with pre-defined patterns or rules. They serve as ‘exception detection ’ methods where the rules or definitions of what might constitute an exception are able to be known and specified ahead of time. Many problems are suited to this approach. Many problems however, especially those of a more complex nature, are not well suited. The rules or definitions simply cannot be specified. For example, in the analysis of transaction data there are no known suspicious transactions. This chapter presents a human-centred network data mining methodology that addresses the issues of depicting implicit relationships between data attributes and/or specific values of these attributes. A case study from the area of security illustrates the application of the methodology and corresponding data mining techniques. The chapter argues that for many problems, a ‘discovery’ phase in the investigative process based on visualisation and human cognition is a logical precedent to, and complement of, more automated ‘exception detection ’ phases

Action Recognition in Videos: from Motion Capture Labs to the Web

This paper presents a survey of human action recognition approaches based on visual data recorded from a single video camera. We propose an organizing framework which puts in evidence the evolution of the area, with techniques moving from heavily constrained motion capture scenarios towards more challenging, realistic, "in the wild" videos. The proposed organization is based on the representation used as input for the recognition task, emphasizing the hypothesis assumed and thus, the constraints imposed on the type of video that each technique is able to address. Expliciting the hypothesis and constraints makes the framework particularly useful to select a method, given an application. Another advantage of the proposed organization is that it allows categorizing newest approaches seamlessly with traditional ones, while providing an insightful perspective of the evolution of the action recognition task up to now. That perspective is the basis for the discussion in the end of the paper, where we also present the main open issues in the area.Comment: Preprint submitted to CVIU, survey paper, 46 pages, 2 figures, 4 table