Stealth and a Transnational Politics of Location in Videogames

This article addresses Inderpal Grewal and Caren Kaplan’s call for transnational feminist research that makes visible “the material conditions that structure women’s lives in diverse locations” (17). The author argues that videogames can contribute to feminist scholarship by creating virtual spaces that simulate how a transnational politics of location plays out on women’s bodies. This article provides a spatial analysis of three videogames, République, Horizon: Zero Dawn, and Alien: Isolation, to show how the games’ procedures can persuade audiences to empathize with the surveillance and precarity of women’s bodies in real-life transnational experiences. While the games focus on “stealth,” the limitations provided by the gameplay simulate the different ways in which women’s bodies must “sneak” around national identities and rules, thus showing the ways in which a transnational politics of location creates “contradictory positions. . . [for women who] inhibit unitary identities” (Grewal and Kaplan 7)

Exploratory search through large video corpora

Activity retrieval is a growing field in electrical engineering that specializes in the search and retrieval of relevant activities and events in video corpora. With the affordability and popularity of cameras for government, personal and retail use, the quantity of available video data is rapidly outscaling our ability to reason over it. Towards the end of empowering users to navigate and interact with the contents of these video corpora, we propose a framework for exploratory search that emphasizes activity structure and search space reduction over complex feature representations. Exploratory search is a user driven process wherein a person provides a system with a query describing the activity, event, or object he is interested in finding. Typically, this description takes the implicit form of one or more exemplar videos, but it can also involve an explicit description. The system returns candidate matches, followed by query refinement and iteration. System performance is judged by the run-time of the system and the precision/recall curve of of the query matches returned. Scaling is one of the primary challenges in video search. From vast web-video archives like youtube (1 billion videos and counting) to the 30 million active surveillance cameras shooting an estimated 4 billion hours of footage every week in the United States, trying to find a set of matches can be like looking for a needle in a haystack. Our goal is to create an efficient archival representation of video corpora that can be calculated in real-time as video streams in, and then enables a user to quickly get a set of results that match. First, we design a system for rapidly identifying simple queries in large-scale video corpora. Instead of focusing on feature design, our system focuses on the spatiotemporal relationships between those features as a means of disambiguating an activity of interest from background. We define a semantic feature vocabulary of concepts that are both readily extracted from video and easily understood by an operator. As data streams in, features are hashed to an inverted index and retrieved in constant time after the system is presented with a user's query. We take a zero-shot approach to exploratory search: the user manually assembles vocabulary elements like color, speed, size and type into a graph. Given that information, we perform an initial downsampling of the archived data, and design a novel dynamic programming approach based on genome-sequencing to search for similar patterns. Experimental results indicate that this approach outperforms other methods for detecting activities in surveillance video datasets. Second, we address the problem of representing complex activities that take place over long spans of space and time. Subgraph and graph matching methods have seen limited use in exploratory search because both problems are provably NP-hard. In this work, we render these problems computationally tractable by identifying the maximally discriminative spanning tree (MDST), and using dynamic programming to optimally reduce the archive data based on a custom algorithm for tree-matching in attributed relational graphs. We demonstrate the efficacy of this approach on popular surveillance video datasets in several modalities. Finally, we design an approach for successive search space reduction in subgraph matching problems. Given a query graph and archival data, our algorithm iteratively selects spanning trees from the query graph that optimize the expected search space reduction at each step until the archive converges. We use this approach to efficiently reason over video surveillance datasets, simulated data, as well as large graphs of protein data

BusTag- Stopping Criminal Damage to London Buses

Vandalism, particularly graffiti, has become a large problem on the public transportation system of London. In order to combat this problem, the Metropolitan Police and Transport for London together created a unit called BusTag. BusTag has been quite successful in apprehending offenders with the use of surveillance cameras on all the buses. The next step in stopping vandalism on buses is in preventing the act before it occurs. To do that, one must understand the motivation behind such crimes. Only with this information can effective prevention methods be established

The user experience of crowds

This thesis is concerned with the user experience of crowds, incorporating issues of comfort, satisfaction, safety and performance within a given crowd situation. Factors that influence the organisation and monitoring of crowd events will be considered. A comprehensive review of the literature revealed that crowd safety, pedestrian flow modeling, public order policing and hooliganism prevention, has received the greatest attention with previous research on crowds. Whereas crowd performance, comfort and satisfaction has received less attention, particularly within spectator events (sporting and music for example). Original research undertaken for this doctoral thesis involved a series of studies: user focus groups, stakeholder interviews, and observational research within event security and organisation. Following on from these investigations, the findings have been integrated with a tool to assist crowd organisers and deliverers during the planning of crowd events, and accompanying user feedback interviews following use of the tool. The overarching aim of the research within this thesis was to explore the complex issues that contribute to the user experience of being in a crowd, and how this might be improved. The crowd user focus groups revealed differences in factors affecting crowd satisfaction, varying according to age and user expectations. Greater differences existed between crowd users, than across crowd situations, highlighting the importance of identifying expected crowd members when planning individual events. Additionally, venue design, organisation, safety and security concerns were found to highly affect crowd satisfaction, irrespective of group differences or crowd situations, showing the importance of these issues when considering crowd satisfaction for all crowd events, for any crowd members. Stakeholder interviews examining crowds from another perspective suggested that overall safety was a high priority due to legal obligations, in order to protect venue reputation. Whereas, comfort and satisfaction received less attention within the organisation of crowd events due to budget considerations, and a lack of concern as to the importance of such issues. Moreover, communication and management systems were sometimes inadequate to ensure compliance with internal procedures. In addition a lack of usable guidance was seen to be available to those responsible for organising crowd situations. Eleven themes were summarised from the data, placed in order of frequency of references to the issues: health and safety, public order, communication, physical environment, public relations, crowd movement, event capacity, facilities, satisfaction, comfort, and crowd characteristics. Results were in line with the weighting of the issues within the literature, with health and safety receiving the most attention, and comfort and satisfaction less attention. These results were used to form the basis of observational checklists for event observations across various crowd situations. Event observations took two forms: observing the role of public and private security, and observing crowd events from the user perspective. Observations within public and private security identified seven general themes: communication, anticipating crowd reaction, information, storage, training, role confusion, financial considerations and professionalism. Findings questioned the clarity of the differing roles of public and private security, and understanding of these differences. Also the increasing use of private over public security within crowd event security, and the differing levels of training and experience within public and private security were identified. Event observations identified fifteen common themes drawn from the data analysis: communication, public order, comfort, facilities, queuing systems, transportation, crowd movement, design, satisfaction, health and safety, public relations, event capacity, time constraints, encumbrances, and cultural differences. Key issues included the layout of the event venue together with the movement and monitoring of crowd users, as well as the availability of facilities in order to reduce competition between crowd users, together with possible links to maintaining public order and reducing anti-social behaviour during crowd events. Findings from the focus groups, interviews, and observations were then combined (to enhance the robustness of the findings), and developed into the Crowd Satisfaction Assessment Tool (CSAT) prototype, a practical tool for event organisers to use during the planning of crowd events. In order to assess proof of concept of the CSAT, potential users (event organisers) were recruited to use the CSAT during the planning of an event they were involved in organising. Semi-structured feedback interviews were then undertaken, to gain insight into the content, usefulness, and usability of the CSAT. Separately human factors researchers were recruited to review the CSAT, providing feedback on the layout and usability of the tool. Feedback interviews suggested the CSAT was a useful concept, aiding communication, and providing organisers with a systematic and methodical structure for planning ahead, prioritising ideas, and highlighting areas of concern. The CSAT was described as being clear and easy to follow, with clear aims, and clear instructions for completion, and was felt to aid communication between the various stakeholders involved in the organisation and management of an event, allowing information to be recorded, stored and shared between stakeholders, with the aim of preventing the loss of crucial information. The thesis concludes with a summary model of the factors that influence crowd satisfaction within crowd events of various descriptions. Key elements of this are the anticipation, facilities, and planning considered before an event, influences and monitoring during an event and reflection after an event. The relevance and impact of this research is to assist the planning of crowd events, with the overall aim of improving participant satisfaction during crowd events. From a business perspective the issue is important with competition between events, the desire to encourage return to events, and to increase profit for organisers. From an ergonomics perspective, there is the imperative of improving the performance of crowd organisers and the experience of crowd users