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Organizations and their actors are increasingly using video surveillance to monitor organizational members, employees, clients, and customers. The use of such technologies in workplaces creates a virtual panopticon and increases uncertainty for those under surveillance. Video surveillance in organizations poses several concerns for the privacy of individuals and creates a security-privacy dilemma for organizations to address. The purpose of this paper is to offer a decision-making model that ties in ethical considerations of access, equality, and transparency at four stages of video surveillance use in organizations: deployment of cameras and equipment, capturing footage, processing and storing data, and editing and sharing video footage. At each stage, organizational actors should clearly identify the purpose for video surveillance, adopt a minimum capability necessary to achieve their goals, and communicate decisions made and actions taken that involve video surveillance in order to reduce uncertainty and address privacy concerns of those being surveilled.

The paper proposes a normative model for ethical video surveillance organizational decision making based on a review of relevant literature and recent events.

The paper provides several implications for the future of dealing with security-privacy dilemmas in organizations and offers structured considerations for corporation leaders and decision makers.

The paper includes implications for organizations to approach video surveillance with ethical considerations for stakeholder privacy while balancing security demands.

This paper offers a framework for decision-makers that also offers opportunities for further research around the concept of ethics in organizational video surveillance.

The high-efficient processing of mass data is a primary issue in building and maintaining security video surveillance system. This paper aims to focus on the architecture of security video surveillance system, which was based on Hadoop parallel processing technology in big data environment.

A hardware framework of security video surveillance network cascaded system (SVSNCS) was constructed on the basis of Internet of Things, network cascade technology and Hadoop platform. Then, the architecture model of SVSNCS was proposed using the Hadoop and big data processing platform.

Finally, we suggested the procedure of video processing according to the cascade network characteristics.

Our paper, which focused on the architecture of security video surveillance system in big data environment on the basis of Hadoop parallel processing technology, provided high-quality video surveillance services for security area.

The growth of police operated surveillance cameras has out-paced the ability of humans to monitor them effectively. Computer vision is a possible solution. An ongoing research project on the application of computer vision within a municipal police department is described. The paper aims to discuss these issues.

Following the demystification of computer vision technology, its potential for police agencies is developed within a focus on computer vision as a solution for two common surveillance camera tasks (live monitoring of multiple surveillance cameras and summarizing archived video files). Three unaddressed research questions (can specialized computer vision applications for law enforcement be developed at this time, how will computer vision be utilized within existing public safety camera monitoring rooms, and what are the system-wide impacts of a computer vision capability on local criminal justice systems) are considered.

Despite computer vision becoming accessible to law enforcement agencies the impact of computer vision has not been discussed or adequately researched. There is little knowledge of computer vision or its potential in the field.

This paper introduces and discusses computer vision from a law enforcement perspective and will be valuable to police personnel tasked with monitoring large camera networks and considering computer vision as a system upgrade.

The study explores the use of video to document police interaction with citizens and its role in the renaissance of a contemporary crisis focused on police use-of-force, race relations, and legitimacy in the United States. The saturation of communication technologies and network access have ushered an era of citizens watching the police, consolidating the new visibility of policing and potentially reorganizing to some degree the power dynamics of traditional police/community relations.

The argument is supported through a triangulated analysis that draws on several data sources about video technology use by both citizens and police, media coverage of police shootings, and public opinion on trends in police excessive force.

The institution of policing is experiencing a legitimacy crisis that is fueled by high-profile police shootings of African Americans by white police officers captured by video technology. The public increasingly expects access to video of police/citizen encounters, which redefines the public’s role in police accountability matters as well as the consequences for police legitimacy.

The theory illuminates the ways in which video has become central to public and official discourse in police use-of-force cases and the problems its presence and absence presents in police/community relations. The ability of citizens to record and widely share video of police encounters is a new development in the ability of citizens and police reform advocates to frame the discourse on police/community relations, accountability, and legitimacy.

Social signal processing under affective computing aims at recognizing and extracting useful human social interaction patterns. Fight is a common social interaction in real life. A fight detection system finds wide applications. This paper aims to detect fights in a natural and low-cost manner.

Research works on fight detection are often based on visual features, demanding substantive computation and good video quality. In this paper, the authors propose an approach to detect fight events through motion analysis. Most existing works evaluated their algorithms on public data sets manifesting simulated fights, where the fights are acted out by actors. To evaluate real fights, the authors collected videos involving real fights to form a data set. Based on the two types of data sets, the authors evaluated the performance of their motion signal analysis algorithm, which was then compared with the state-of-the-art approach based on MoSIFT descriptors with Bag-of-Words mechanism, and basic motion signal analysis with Bag-of-Words.

The experimental results indicate that the proposed approach accurately detects fights in real scenarios and performs better than the MoSIFT approach.

By collecting and annotating real surveillance videos containing real fight events and augmenting with well-known data sets, the authors proposed, implemented and evaluated a low computation approach, comparing it with the state-of-the-art approach. The authors uncovered some fundamental differences between real and simulated fights and initiated a new study in discriminating real against simulated fight events, with very good performance.

To discuss and review the shift to computer enhanced self‐monitoring CCTV surveillance systems of public spaces and the social implications of this shift.

A review of the research and evaluation literature concerning CCTV surveillance systems culling out the history of public space CCTV systems and the concerns associated with first and second generation CCTV surveillance.

The main difference between first and second generation surveillance is the change from a “dumb camera” that needs a human eye to evaluate its images to a computer‐linked camera system that evaluates its own video images. Second generation systems reduce the human factor in surveillance and address some of the basic concerns associated with first generation surveillance systems such as data swamping, boredom, voyeurism, and profiling. Their enhanced capabilities, though, raise new concerns, particularly the expansion of surveillance and its intrusiveness.

Additional research is needed to assess CCTV surveillance on a set of social dynamics such as informal guardianship activities by citizens.

The adoption of computer‐enhanced CCTV surveillance systems should not be an automatic response to a public space security problem and their deployment should not be decided simply on the technology's availability or cost.

This paper provides a concise overview of the concerns associated with first generation CCTV surveillance and how the evolution of computer‐enhanced CCTV surveillance systems will alter and add to these concerns. For researchers it details research questions that need to be addressed. For practitioners and government officials considering the use of public space CCTV surveillance it provides a set of issues that should be considered prior to system adoption or deployment.

This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies.

This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context.

This conceptual paper concentrates on presenting a model to assist managers to weigh ethical considerations against the security benefits to the organization when assessing the use of video surveillance equipment. The three key dimensions here are transparency, access, and equality.

The paper provides strategic insights and practical thinking that have influenced some of the world’s leading organizations.

The briefing saves busy executives and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

The purpose of this paper is to explore the potential and adoption of closed-circuit television (CCTV) surveillance-based security system (hereafter “CCTV”) for enhancing the security of library materials in academic libraries of universities (central, state, deemed and private) and prestigious institutions such as Indian Institutes of Technology and Indian Institutes of Management in a developing country, i.e. India. The study also overviewed the CCTV policies of the studied libraries of universities/institutions as they relate to the ethical aspects of the surveillance system.

Structured questionnaire was designed and distributed among librarians of 24 academic libraries covering each zone of India in October 2019 in both physical and online manner. All 24 filled-in questionnaires were collected personally and online by the investigator were found valid eliciting a response rate of 100%. All the 24 filled-in questionnaires were included in the analysis of the interpretation of data. The response to 18 questions was analyzed in the form of tables and figures using descriptive statistical methods.

The study reveals that librarians’ found CCTV useful for security by controlling theft, unethical losses and missing items. It also helped to curb mutilation and vandalism, procurement of the rare material via the latest camera devices and night vision capturing, besides improving the service efficiency of the patron, as well as staff. The quantitative study surveyed security professionals to assess how each university/institution developed, deployed and integrated CCTV policies related to securing video data, safeguarding privacy and prevention of the potential for the unethical use of surveillance cameras. The analysis of the survey responses determined that more than 50% of the universities/institutions participating had a written CCTV policy. Further, library professionals find that the future of libraries lies in a CCTV system, so the cost should be brought down to improve return on investment by the mass adoption of this technology in a developing country such as India.

The findings of the study showed that the potential uses of CCTV in Indian libraries are slow compared to that of the libraries of developed countries and some of the developing countries. Many of the CCTV policies that universities/institutions did have failed to include mandated training of personnel or provisions ensuring that their policies remained up-to-date. It is suggested that universities and institutions understudy should realize the benefits of CCTV systems and incorporate-related updated tools in the security and multi-purpose uses in the libraries to enhance the services for the users and security for the materials or collections.

The paper includes implications for libraries and their professionals to approach CCTV systems with ethical considerations for procurement of library collections, which help to detect mutilation/theft, observe the misbehavior of users, as well as staff and deployment, should not be decided merely while balancing security demands.

The study is significant because it represents one of the earliest works to shed light on the current level of the use of CCTV system by librarians of studied libraries of universities/institutes in developing country such as India and how they are providing CCTV-based security and services, which are currently in its primitive nature. The study also suggested that select libraries are required to weigh up and balance many competing desires, demands and objectives.

This paper provides a concise overview of the various applications/area and uses of CCTV system including its procedures during implementation, merits and demerits while using the system described above in libraries and recommends this technology to other libraries for faster and better services for their users and security to their library materials in today’s technological advancement. It provides a set of issues that should be considered before system adoption or deployment.

Object detection models have gained considerable popularity as they aid in lot of applications, like monitoring, video surveillance, etc. Object detection through the video tracking faces lot of challenges, as most of the videos obtained as the real time stream are affected due to the environmental factors.

This research develops a system for crowd tracking and crowd behaviour recognition using hybrid tracking model. The input for the proposed crowd tracking system is high density crowd videos containing hundreds of people. The first step is to detect human through visual recognition algorithms. Here, a priori knowledge of location point is given as input to visual recognition algorithm. The visual recognition algorithm identifies the human through the constraints defined within Minimum Bounding Rectangle (MBR). Then, the spatial tracking model based tracks the path of the human object movement in the video frame, and the tracking is carried out by extraction of color histogram and texture features. Also, the temporal tracking model is applied based on NARX neural network model, which is effectively utilized to detect the location of moving objects. Once the path of the person is tracked, the behaviour of every human object is identified using the Optimal Support Vector Machine which is newly developed by combing SVM and optimization algorithm, namely MBSO. The proposed MBSO algorithm is developed through the integration of the existing techniques, like BSA and MBO.

The dataset for the object tracking is utilized from Tracking in high crowd density dataset. The proposed OSVM classifier has attained improved performance with the values of 0.95 for accuracy.

This paper presents a hybrid high density video tracking model, and the behaviour recognition model. The proposed hybrid tracking model tracks the path of the object in the video through the temporal tracking and spatial tracking. The features train the proposed OSVM classifier based on the weights selected by the proposed MBSO algorithm. The proposed MBSO algorithm can be regarded as the modified version of the BSO algorithm.

Citizens often perceive surveillance by government authorities as oppressive and, hence, demonstrate reluctance in value co-creation from such services. This study aims to investigate the challenges and benefits of citizen empowerment through technology-driven surveillance or “smart surveillance.”

Guided by Dynamic Capability theory, the authors conduct in-depth interviews with officers in-charge of surveillance in smart cities. Given the contemporary advancements, this approach allows a retrospective and real-time understanding of interviewees’ experiences with smart surveillance.

The authors develop five propositions for citizen empowerment through smart surveillance to summarize the findings of this study.

This study advances the relevance of Dynamic Capability in public administration.

Smart city authorities and policymakers may leverage the insights provided in this study to design appropriate policies for smart surveillance.

The authors find that factors such as digital technology and infrastructure, information management, skill divide and perceived return on investment may influence citizen empowerment through smart surveillance.