مقالات انگلیسی

It is estimated that there are five million CCTV cameras in use today. CCTV is used by a wide range of organisations and for an increasing number of purposes. Despite this, there has been little research to establish whether these systems are fit for purpose. This thesis takes a socio-technical approach to determine whether CCTV is effective, and if not, how it could be made more effective. Humancomputer interaction (HCI) knowledge and methods have been applied to improve this understanding and what is needed to make CCTV effective; this was achieved in an extensive field study and two experiments. In Study 1, contextual inquiry was used to identify the security goals, tasks, technology and factors which affected operator performance and the causes at 14 security control rooms. The findings revealed a number of factors which interfered with task performance, such as: poor camera positioning, ineffective workstation setups, difficulty in locating scenes, and the use of low-quality CCTV recordings. The impact of different levels of video quality on identification and detection performance was assessed in two experiments using a task-focused methodology. In Study 2, 80 participants identified 64 face images taken from four spatially compressed video conditions (32, 52, 72, and 92 Kbps). At a bit rate quality of 52 Kbps (MPEG-4), the number of faces correctly identified reached significance. In Study 3, 80 participants each detected 32 events from four frame rate CCTV video conditions (1, 5, 8, and 12 fps). Below 8 frames per second, correct detections and task confidence ratings decreased significantly. These field and empirical research findings are presented in a framework using a typical CCTV deployment scenario, which has been validated through an expert review. The contributions and limitations of this thesis are reviewed, and suggestions for how the framework should be further developed are provided. The journey one must make to earn a PhD can be very lonely. I am fortunate to have had the support of many people from academia and industry along the way. I am sincerely indebted and thankful to all of them. This work could not have come together without their help. I would like to acknowledge that this PhD research was funded by the European Physical Science Research Council (EPSRC) 2004–2007, grant no. EP1P50064811. I am most grateful to my dedicated supervisors Prof. M. Angela Sasse and Dr Simon Prince. Angela has given me great confidence, encouragement, guidance, and a tremendous amount of support throughout my research studies. I would like to thank my second supervisor, Simon, who kindly gave me advice and constructive comments on the empirical parts of my research. A very big thank you goes to Hendrik Knoche, my official PhD mentor, colleague, and friend. Hendrik provided me with guidance on my video quality experiments and taught me a great deal about video, imaging and data analysis. Thank you to Dimitris Miras who provided feedback on my early experimental ideas and offered his expertise on video quality. I would also like to thank Dr Paul Cairns (formerly of UCLIC and now at York University) who was so willing to offer his time to review my research papers and offer guidance on data analysis for my empirical experiments – even on short notice.