Title: An approach for designing a real-time intelligent distributed surveillance system
Author: Valera Espina, Maria
Awarding Body: Kingston University
Current Institution: Kingston University
Date of Award: 2006
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EThOS Persistent ID: uk.bl.ethos.431490 
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
Abstract:
The main aim of this PhD is to investigate how a methodology rooted in systems engineering concepts can be established and applied to the design of distributed wide-area visual surveillance systems. Nowadays, the research community in surveillance systems tends to be mostly focused on the computer vision part of these systems, researching and developing more intelligent algorithms. The integration and finally the creation of the system per se, are usually regarded as a secondary priority. We postulate here that until a robust systems-centred, rather than algorithmic-centred approach is used, the realisation of realistic distributed surveillance systems is unlikely to happen. The future generation of surveillance systems can be categorised, from a system engineering point of view, as concurrent, distributed, embedded, real time systems. An important aspect of these systems is the inherent temporal diversity (heterogeneous timing) that arises from a variety of timing requirements and from the parallelisation and distribution of the processes that compose the system. Embedded, real-time systems are often naturally asynchronous. However, the computer vision part of these surveillance systems is commonly conceived and designed in a sequential and synchronous manner, in many cases using an object-oriented approach. Moreover, to cope with the distributed nature of these systems, technologies such as CORBA are applied. Designing processes in a synchronous manner plus the run-time overheads associated with object oriented implementations may cause communication bottlenecks. Perhaps more importantly, it may produce unpredictable behaviour of some components of the system and hence undetermined performance from a system as a whole. Clearly, this is a major problem on surveillance systems that can often be expected to be safety-critical. This research has explored the use of an alternative approach to object-orientation for the design and implementation of intelligent distributed surveillance systems. The approach is known as Real-Time Networks (exemplified by system engineering methodologies such as MASCOT and extensions such as DORIS). This approach is based conceptually on conceiving solutions as being naturally concurrent, from the highest level of abstraction, with concurrent activities communicating through well-defined data-centred mechanisms. The methodology favours a disciplined approach to design, which yields a modular structure that has close correspondence between functional elements in design and constructional elements for system integration. It is such characteristics that we believe will become essential in overcoming the complexities of going from small-scale computer vision prototypes to large-scale working systems. To justify the selection of this methodology, an overview of different software approach methods that may be used for designing wide-area intelligent surveillance systems is given. This is then, narrowed down to a comparison between Real-Time Networks and Object Orientation. The comparison is followed by an illustration of two different design solutions of an existing real-time distributed surveillance system called ADVISOR. One of the design solutions, based on Object Oriented concepts, uses CORBA as a means for the integration and distribution characteristics of the system. The other design solution, based on Real-Time Networks, uses DORIS methodology as a solution for the design of the system. Once the justification over the selection is done, a' novel design of a generic visual surveillance system using the proposed Real-Time Networks method is presented. Finally, the conclusions and future work are explained in the last chapter.
Keywords: Computer science and informatics
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