La Universidad Nacional de Tumbes reconoce la necesidad de fortalecer la Seguridad de sus Instalaciones mejorando, el Control y la Vigilancia, con elfin de garantizar en lo posible la Protección de sus Bienes, equipo y personas. Las medidas adoptadas actualmente para la protección del Campus son básicas careciendo de tecnología para su labor efectiva. El proyecto aborda la problemática de Seguridad con un enfoque moderno y amplio incorporando la instalación en el Campus de un circuito cerrado de televisión implementado por etapas como pieza básica, que integrado a otros equipos y materiales de última generación, ayudaran a mejorar la calidad de las acciones de control y vigilancia del Campus facilitando al personal encargado de la seguridad un conjunto de medios destinados a optimizar su desempeño y ofrece a las autoridades universitarias el acceso remoto al sistema con el fin de supervisar la marcha del servicio en tiempo real.

The ubiquitous nature of CCTV Surveillance cameras means substantial amounts of data being generated. In case of an investigation, this data must be manually browsed and analysed in search of relevant information for the case. As an example, it took more than 450 detectives to examine the hundreds of thousands of hours of videos in the investigation of the 2011 London Riots: one of the largest the London's MET police has ever seen. Anything that can help the security forces save resources in investigations such as this, is valuable. Consequently, automatic analysis of surveillance scenes is a growing research area. One of the research fronts tackling this issue, is the semantic understanding of the scene. In this, the output of computer vision algorithms is fed into Semantic Frameworks, which combine all the information from different sources and try to reach a better knowledge of the scene. However, representing and reasoning with imprecise and uncertain information remains an outstanding issue in current implementations. The Demspter-Sha er (DS) Theory of Evidence has been proposed as a way to deal with imprecise and uncertain information. In this thesis we use it for the main contributions. In our rst contribution, we propose the use of the DS theory and its Transferable Belief Model (TBM) realisation as a way to combine Bayesian priors, using the subjectivist view of the Bayes' Theorem, where the probabilities are beliefs. We rst compute the a priori probabilities of all the pair of events in the model. Then a global potential is created for each event using the TBM. This global potential will encode all the prior knowledge for that particular concept. This has the bene t that when this potential is included in a knowledge base because it has been learned, all the knowledge it entails comes with it. We also propose a semantic web reasoner based on the TBM. This reasoner consists of an ontology to model any domain knowledge using the TBM constructs of Potentials, Focal Elements, and Con gurations. The reasoner also consists of the implementations of the TBM operations in a semantic web framework. The goal is that after the model has been created, the TBM operations can be applied and the knowledge combined and queried. These operations are computationally complex, so we also propose parallel heuristics to the TBM operations. This allows us to apply this paradigm on problems of thousands of records. The nal contribution, is the use of the TBM semantic framework with the method to combine the prior knowledge to detect riots on CCTV footage from the 2011 London riots. We use around a million and a half manually annotated frames with 6 di erent concepts related to the riot detection task, train the system, and infer the presence of riots in the test dataset. Tests show that the system yields a high recall, but a low precision, meaning that there are a lot of false positives. We also show that the framework scales well as more compute power becomes available.

Public street surveillance, a domain of Closed Circuit Television (CCTV), has grown enormously and is becoming common place with increasing utilization in society as an all-purpose security tool. Previous authors (Ditton, 1999; Davies, 1998; Horne, 1998; Tomkins, 1998) have raised concern over social, civil and privacy issues, but there has been limited research to quantify these concerns. There are a number of core aspects that could relocate the risk perception and therefore, social support of public street surveillance. This study utilized the psychometric paradigm to quantitatively measure the social risk perception of public street surveillance. The psychometric paradigm is a method that presents risk perception in a two factor representation, being dread risk and familiarity to risk. Four additional control activities and technologies were tested, being radioactive waste, drinking water chlorination, coal mining disease and home swimming pools. Analysis included spatial representation, and multidimensional scaling (MDS) Euclidean and INDSCAL methods. The study utilized a seven point Likert scale, pre and post methodology, and had a target population of N=2106, with a sample of N=135 (alpha=0.7).

Naujųjų technologijų pažanga, radikaliai keičia ir požiūrį į tam tikras nuo seno visuomenėje susiformavusias vertybes. Šiomis dienomis visuomenė jaučiasi vis labiau stebima. Siekiant viešųjų interesų (visuomenės saugumo, nusikalstamumo mažinimo ir pan.) privačiose ir viešosiose erdvėse yra įrengiamos vaizdo stebėjimo kameros, kurių užfiksuoti duomenys yra nuolat transliuojami bei kaupiami. Čia yra susiduriama su asmens privatumo užtikrinimo problema. Magistriniame darbe yra kalbama apie teisės į privatumą užtikrinimą vaizdo stebėjimo priemonių panaudojimo kontekste. Teisė į privatumą yra ganėtinai jauna pasaulio teisinėje sistemoje, teisiškai įtvirtinta 1950 m. Europos žmogaus teisių ir pagrindinių laisvių apsaugos konvencijos (Konvencija) 8 straipsnyje. Asmens duomenų teisinė apsauga – teisės į privatumą elementas. Vaizdo stebėjimo priemonių panaudojimo atveju yra neišvengiamai susiduriama ir su asmens duomenų (vaizdo duomenų) teisinės apsaugos problemomis. Tad darbe analizuojamas ne tik Konvencijos aštuntasis straipsnis, nubrėžiantis pagrindines gaires privatumo apsaugai vaizdo stebėjimo priemonių panaudojimo atveju, yra aptariami ir asmens duomenų teisinę apsaugą reglamentuojantys Europos Sąjungos bei Lietuvos Respublikos teisiniai dokumentai (Direktyva 95/46/EB, Lietuvos Respublikos asmens duomenų teisinės apsaugos įstatymas). Darbas suskirstytas į tris struktūrines dalis. Pirmoje jų yra aptariam privatumo samprata, antrojoje aptariama vaizdo stebėjimo priemonių samprata... [toliau žr. visą tekstą] / The advancement of new technologies is radically changing the world. Nowadays society is a transparent society. In recent years, the use of video surveillance cameras (also called Closed Circuit Television, or CCTV) throughout the world has grown to unprecedented levels. And there we find out many problems, concerning protection of an individuals private life. The work discusses the issue of right to private life protection in a context of video surveillance. The right to private life is quite young in world’s legitimate system and especially in Lithuanian law system. Personal data protection as a part of privacy right is an aspect of human rights. This proposition is universally accepted. As long ago as 1948, privacy was given recognition in the Universal Declaration of Human Rights. In 1950, privacy was implemented in European Convention of Human Rights. This work is divided into three parts. One of them is talking about a conception of a privacy, separates data protection conception from right to private law, the second one is talking about video surveillance systems in general, their technical capacity, the last one is talking about European Convention of Human Rights and its article 8 as the main principle which is a sound base for European Union and Lithuanian regulation of video surveillance, analysis Charter of Fundamental Rights of the European Union, Directive 95/46/EC of the European Union, Constitution of Lithuania, Lithuanian Data Protection Law in the context of... [to full text]

The research contributes to the field of video analysis by proposing novel approaches to automatically generating human observer performance patterns that can be effectively used in advancing the modern video analytic and forensic algorithms. Eye tracker and eye movement analysis technology are employed in medical research, psychology, cognitive science and advertising. The data collected on human eye movement from the eye tracker can be analyzed using the machine and statistical learning approaches. Therefore, the study attempts to understand the visual attention pattern of people when observing a captured CCTV footage. It intends to prove whether the eye gaze of the observer which determines their behaviour is dependent on the given instructions or the knowledge they learn from the surveillance task. The research attempts to understand whether the attention of the observer on human objects is differently identified and tracked considering the different areas of the body of the tracked object. It attempts to know whether pattern analysis and machine learning can effectively replace the current conceptual and statistical approaches to the analysis of eye-tracking data captured within a CCTV surveillance task. A pilot study was employed that took around 30 minutes for each participant. It involved observing 13 different pre-recorded CCTV clips of public space. The participants are provided with a clear written description of the targets they should find in each video. The study included a total of 24 participants with varying levels of experience in analyzing CCTV video. A Tobii eye tracking system was employed to record the eye movements of the participants. The data captured by the eye tracking sensor is analyzed using statistical data analysis approaches like SPSS and machine learning algorithms using WEKA. The research concluded the existence of differences in behavioural patterns which could be used to classify participants of study is appropriate machine learning algorithms are employed. The research conducted on video analytics was perceived to be limited to few iii projects where the human object being observed was viewed as one object, and hence the detailed analysis of human observer attention pattern based on human body part articulation has not been investigated. All previous attempts in human observer visual attention pattern analysis on CCTV video analytics and forensics either used conceptual or statistical approaches. These methods were limited with regards to making predictions and the detection of hidden patterns. A novel approach to articulating human objects to be identified and tracked in a visual surveillance task led to constrained results, which demanded the use of advanced machine learning algorithms for classification of participants The research conducted within the context of this thesis resulted in several practical data collection and analysis challenges during formal CCTV operator based surveillance tasks. These made it difficult to obtain the appropriate cooperation from the expert operators of CCTV for data collection. Therefore, if expert operators were employed in the study rather than novice operator, a more discriminative and accurate classification would have been achieved. Machine learning approaches like ensemble learning and tree based algorithms can be applied in cases where a more detailed analysis of the human behaviour is needed. Traditional machine learning approaches are challenged by recent advances in the field of convolutional neural networks and deep learning. Therefore, future research can replace the traditional machine learning approaches employed in this study, with convolutional neural networks. The current research was limited to 13 different videos with different descriptions given to the participants for identifying and tracking different individuals. The research can be expanded to include any complicated demands with regards to changes in the analysis process.

This research evaluates crime prevention effects/impact of open-street closed circuit television (CCTV) surveillance systems as installed in the selected areas (research sites) of the cities of Johannesburg and Tshwane in the Gauteng Province of South Africa on crimes occurring in these surveilled areas. Currently, CCTV surveillance systems are a common sight in many of the urban areas of South Africa.The principal aim of this study was to explore the evaluation of CCTV for crime prevention, reduction and control. The results show that, despite a lack of empirical evidence as to the value of CCTV surveillance systems in preventing or reducing crime, there is strong public support for these systems and that the foundation for much of this support lies in the perceptions/feelings of members of the public of greater safety generated in areas with CCTV coverage. The method of sampling used was a purposive non-probability sampling approach. Participants were selected for interviews based on their knowledge and experience of CCTV systems. The results show that, despite this lack of empirical evidence, CCTV appears to be a viable option for crime prevention and control when integrated with evidence-based strategies rather than as a stand-alone tactic in order to achieve crime control benefits. / Criminology and Security Science / M. Tech. (Security Management)

No description available.

No description available.

This research aimed to explore whether the recognition of offenders with a concealed firearm by a human operator might be based on the recognition of affective (negative) state derived from non-verbal behaviour that is accessible from CCTV images. Since a firearm is concealed, it has been assumed that human observers would respond to subtle cues which individuals inherently produce whilst carrying a hidden firearm. These cues are believed to be reflected in the body language of those carrying firearms and might be apprehended by observers at a conscious or subconscious level. Another hypothesis is that the ability to recognize the carrier of concealed firearm in the CCTV footage might be affected by other factors, such as the skills in decoding an affective state of others and the viewpoint of observation of the surveillance targets. In order to give a theoretical and experimental basis for these hypotheses the first objective was to examine the extant literature to determine what is known about recognition of affect from non-verbal cues (e.g. facial expressions and body movement), and how it can be applied to the detection of human mal-intent. A second objective was to explore this subject in relation to the detection of concealed firearm carrying through performing a number of experimental studies. The studies employed experts, i.e. CCTV operators and mainly the lay people as participants. Also, various experimental techniques such as questionnaires and eye-tracking registration were used to investigate the topic. The results show that human observers seem to use visual indicators of affective state of surveillance targets to make a decision whether or not the individuals are carrying a concealed firearm. The most prominent cues were face, and upper body of surveillance targets, gait, posture and arm movements. The test of decoding ability did not show sufficient relationship with the ability to detect a concealed firearm bearer. The performance on the task might be view dependent. Further research into this topic will be needed to generate strategies that would support reliable detection of concealed firearm carrying through employing of related affective behavioural cues.

China’s official media are nearly a decade into a global expansion programme to challenge the dominance of Anglo-American news organisations and their framing of world events. This research tackles the questions of whether Chinese media abroad deserve to be dismissed as channels for Communist Party propaganda, whether their output has journalistic merit, and whether Chinese journalism has a different character from that of the Anglosphere. The focus is on CCTV-News in English, whose ‘hard news’ output is compared with that of BBC World News TV between 2014 and 2016: previous studies of the channel have concentrated on single regions or events, political strategy or current affairs. Comparative quantitative content analysis of five constructed weeks of news is followed by frame analysis of selected events with a framework adapted to accommodate Chinese political and cultural proclivities. Subconscious editorial judgements are made manifest through a pioneering experimental technique, ‘cross-editing’, in which journalists from Britain and China swap broadcast news scripts and re-edit them as if for output on their own channel. Topics of strategic importance to Beijing are the focus of the research: news about China, and coverage of Africa including China in Africa. The empirical analysis confirms that these politically sensitive areas are handled by CCTV-News mainly in ways that are alien to editorial principles in the Anglosphere, either through lack of journalistic rigour (partial reporting and ‘positive news’) or through differences in framing such as solution-focused reporting and aversion to conflict. The analysis demonstrates the uneven editorial imperatives across CCTV-News and the improvised nature of journalistic professionalism, including how far Chinese reporters dare push the boundaries of information control. In the BBC World News output, the comparative methods reveal weaknesses in the Corporation’s professed tenets of balance and impartiality, and highlight the difficulties of telling nuanced, non-pictorial stories from distant countries while shackled by Anglo-American television ‘grammar’. The research confirms the considerable impediments to credibility occasioned by political control over CCTV’s English news output: however, it also indicates that the journalism of the Anglosphere, in the form of BBC World News, is not the universal standard many believed it to be.