67 research outputs found

    Recent Developments in Video Surveillance

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    With surveillance cameras installed everywhere and continuously streaming thousands of hours of video, how can that huge amount of data be analyzed or even be useful? Is it possible to search those countless hours of videos for subjects or events of interest? Shouldn’t the presence of a car stopped at a railroad crossing trigger an alarm system to prevent a potential accident? In the chapters selected for this book, experts in video surveillance provide answers to these questions and other interesting problems, skillfully blending research experience with practical real life applications. Academic researchers will find a reliable compilation of relevant literature in addition to pointers to current advances in the field. Industry practitioners will find useful hints about state-of-the-art applications. The book also provides directions for open problems where further advances can be pursued

    Multivariate Analysis in Management, Engineering and the Sciences

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    Recently statistical knowledge has become an important requirement and occupies a prominent position in the exercise of various professions. In the real world, the processes have a large volume of data and are naturally multivariate and as such, require a proper treatment. For these conditions it is difficult or practically impossible to use methods of univariate statistics. The wide application of multivariate techniques and the need to spread them more fully in the academic and the business justify the creation of this book. The objective is to demonstrate interdisciplinary applications to identify patterns, trends, association sand dependencies, in the areas of Management, Engineering and Sciences. The book is addressed to both practicing professionals and researchers in the field

    An Evaluation of multispectral earth-observing multi-aperture telescope designs for target detection and characterization

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    Earth-observing satellites have fundamental size and weight design limits since they must be launched into space. These limits serve to constrain the spatial resolutions that such imaging systems can achieve with traditional telescope design strategies. Segmented and sparse-aperture imaging system designs may offer solutions to this problem. Segmented and sparse-aperture designs can be viewed as competing technologies; both approaches offer solutions for achieving finer resolution imaging from space. Segmented-aperture systems offer greater fill factor, and therefore greater signal-to-noise ratio (SNR), for a given encircled diameter than their sparse aperture counterparts, though their larger segments often suffer from greater optical aberration than those of smaller, sparse designs. Regardless, the use of any multi-aperture imaging system comes at a price; their increased effective aperture size and improvement in spatial resolution are offset by a reduction in image quality due to signal loss (less photon-collecting area) and aberrations introduced by misalignments between individual sub-apertures as compared with monolithic collectors. Introducing multispectral considerations to a multi-aperture imaging system further starves the system of photons and reduces SNR in each spectral band. This work explores multispectral design considerations inherent in 9-element tri-arm sparse aperture, hexagonal-element segmented aperture, and monolithic aperture imaging systems. The primary thrust of this work is to develop an objective target detection-based metric that can be used to compare the achieved image utility of these competing multi-aperture telescope designs over a designated design parameter trade space. Characterizing complex multi-aperture system designs in this way may lead to improved assessment of programmatic risk and reward in the development of higher-resolution imaging capabilities. This method assumes that the stringent requirements for limiting the wavefront error (WFE) associated with multi-aperture imaging systems when producing imagery for visual assessment, can be relaxed when employing target detection-based metrics for evaluating system utility. Simple target detection algorithms were used to determine Receiver Operating Characteristic (ROC) curves for the various simulated multi-aperture system designs that could be used in an objective assessment of each system\u27s ability to support target detection activities. Also, a set of regressed equations was developed that allow one to predict multi-aperture system target detection performance within the bounds of the designated trade space. Suitable metrics for comparing the shapes of two individual ROC curves, such as the total area under the curve (AUC) and the sample Pearson correlation coefficient, were found to be useful tools in validating the predicted results of the trade space regression models. And lastly, some simple rules of thumb relating to multi-aperture system design were identified from the inspection of various points of equivalency between competing system designs, as determined from the comparison metrics employed. The goal of this work, the development of a process for simulating multi-aperture imaging systems and comparing them in terms of target detection tasks, was successfully accomplished. The process presented here could be tailored to the needs of any specific multi-aperture development effort and used as a tool for system design engineers

    Computational Estimation by Scientific Data Mining with Classical Methods to Automate Learning Strategies of Scientists

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    Sensor Signal and Information Processing II

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    In the current age of information explosion, newly invented technological sensors and software are now tightly integrated with our everyday lives. Many sensor processing algorithms have incorporated some forms of computational intelligence as part of their core framework in problem solving. These algorithms have the capacity to generalize and discover knowledge for themselves and learn new information whenever unseen data are captured. The primary aim of sensor processing is to develop techniques to interpret, understand, and act on information contained in the data. The interest of this book is in developing intelligent signal processing in order to pave the way for smart sensors. This involves mathematical advancement of nonlinear signal processing theory and its applications that extend far beyond traditional techniques. It bridges the boundary between theory and application, developing novel theoretically inspired methodologies targeting both longstanding and emergent signal processing applications. The topic ranges from phishing detection to integration of terrestrial laser scanning, and from fault diagnosis to bio-inspiring filtering. The book will appeal to established practitioners, along with researchers and students in the emerging field of smart sensors processing

    MORPHOLOGY OF THE FACE AS A POSTMORTEM PERSONAL IDENTIFIER

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    The human face carries some of the most individualizing features suitable for the personal identification. Facial morphology is used for the face matching of living. An extensive research is conducted to develop the matching algorithm to mimic the human ability to recognize and match faces. Human ability to recognize and match faces, however, is not errorless and it serves as the main argument precluding the visual facial matching from its use as an identification tool. The human face keeps its individuality after death. Compared to the faces of living, the faces of deceased are rarely used or researched for the face matching. Different factors influence the appearance of the face of the deceased compared to the face of the living, namely the early postmortem changes and decomposition process. On the other hand, the literature review showed the use of visual recognition in multiple cases of identity assessment after the natural disasters. Presented dissertation thesis is composed of several projects focused on the possibility of personal identification of the decedents solely based on the morphology of their face. Dissertation explains the need for such identification and explores the error rates of the visual recognition of deceased, the progress of facial changes due to the early decomposition and the possibility of utilization of soft biometric traits, specifically facial moles. Lastly, the dissertation presents the use of shape index (s) as a quality indicator of three different 3D scanners aimed towards the most suitable method for obtaining facial postmortem 3D images

    Computational intelligence approaches to robotics, automation, and control [Volume guest editors]

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    A GIS-based decision support tool for optimisation of marine cage siting for aquaculture: A case study for the Western Isles, Scotland.

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    Scotland’s coastal environment has many areas which are potentially suitable for sustainable aquaculture development. However previous studies have shown that aquaculture may have a detrimental impact on sensitive environments. The main objective of this study is to develop a holistic management tool for sustainable coastal marine aquaculture in the Western Isles of Scotland through development of a multi-faceted holistic model that allows consideration of sensitive environments. As the Scottish Government promotes better collaboration and integration of all involved in coastal zone governance (Baxter et al, 2008) this study illustrates the benefits to be gained from harmonized management of information in a Geographical Information System. GIS models are strong support tools designed to aid decision-making. The main strengths are that GIS can generate easily understandable visual displays of results which are based on robust models capable of incorporating vast amounts of spatial data and which can be predictive and can simulate future coastal environment scenarios. Within this study it is demonstrated that GIS-based models can successfully manage and manipulate a wide range of datasets that are essential components in the determination and management of suitable aquaculture locations. The GIS decision support tools evaluated and integrated in this study were based on four main sub models. These were Cage Site Suitability, Particulate Dispersion, Sensitivity Biodiversity Indicators and Visual Landscape Capacity. Exploration of a combination of these sub-models into an overall decision support system was also completed. All sub models developed were flexible, instrumentally coherent and communicatively balanced for the management and planning of the coastal environment . A sub-model was designed to evaluate and optimize the location of marine cage systems. This required development of data layers and modelled sub-components relevant to the important environmental and engineering factors affecting cage designs which included wave climate, bathymetric and substrate profiles. Three cage types were explored; those designed for sheltered, semi-exposed and exposed areas. These environmental factor layers were combined through weighting and Multi criteria evaluation consideration for each cage type. The resulting three sub-models indicated that while the archipelago has quite restricted development potential for cages designed for sheltered environments (91km2), there is a limited development potential for cages designed for semi exposed environments (1543km2) and an optimal potential for aquaculture development with cages designed for exposed environments (3103km2). The greatest potential environmental impact from aquaculture comes from particulate dispersion. Currently, assessing footprints of effect from fish farms is carried out on an individual site basis mostly at ten metre resolution. The sub-model successfully developed in this work resulted in a partially validated multisite particulate sub model at one metre resolution which implemented maximum current velocity as the friction/force image. The sub-model was run on a range of coastal loch fjord systems and demonstrated the variation in particulate dispersion patterns in each fjord system. In all the fjord systems modelled, even where farm sites are close neighbours, there appears to be minimal interaction in the particulate dispersion. While the particulate sub-model is effective and rapid to deploy for multiple sites, it requires further development in order to incorporate the quantitative aspects of particulate dispersion. Aquaculture biodiversity sensitivity indicators were evaluated and five main sub-components were developed; Species sensitive to Aquaculture, Endangered species, Species important to the Western Isles, important spawning and nursery areas and Protected Areas. The sub-model was constructed by combining these layers through weighting and Multicriteria evaluation. The outcomes indicated that within the study area there are 1168km2 (4% of study area) which are highly sensitive to aquaculture activity, although 20595km2 (65% of study area) has a biodiversity that is much less sensitive to aquaculture. This sub-model, and some of its components, can operate as a “stand alone” tool or can be combined into a larger framework. Little modification and re-parameterisation would be required to enable models to be developed to cover the whole of the Scottish coastline, or other coastal locations. Aquaculture can visually affect landscapes, seascapes and can adversely affect visual capacity of different areas. GIS was successfully applied to investigate this contentious issue. This comprehensive and flexible sub-model successfully develops Seascape and Landscape sensitivity analysis of aquaculture structures and also incorporated a novel approach to visual assessment through use of proportional assessment. Combining the sensitivity layers, 6448km2 of the waters of the archipelago (20% of study area) were categorized as having high capacity to incorporate new aquaculture developments, whilst 3301km2 (10% of study area) have a moderate capacity for new aquaculture structures and 1324km2 (4% of study area) have a low capacity for new developments. An overall conceptual framework was designed to explore two methods for the combination of the major sub-models in order to identify the most appropriate areas for sustainable aquaculture with consideration of possible conflicts including conservation issues. Initial evaluations involved the extraction of information from the component GIS sub-models into a structured database. The extracted data provides a range of information that can be used for statistical analysis and decision support, but which leaves the evaluation of the optimal siting of aquaculture at any location in the Western Isles in the hands of the database interrogator. The second method involved combining the sub-models within GIS whole considering trade offs in relation to conservation. This GIS combination of models indicated that, taking many factors into consideration, the Western Isles has 748km2 (2.5% of study area) appropriate for aquaculture development when implementing the C315 and whilst considering the interactions with conservation areas. There were 498km2 (1.6% of study area) appropriate for development when implementing the intermediate C250 cage types but only 15km2 (0.04% of study area) were appropriate for development based on the LMS cage designs for sheltered environments. Both analytical approaches had strengths and weakness and clearly both need to be used in combination to maximise the benefit of the GIS model outcomes. This study has demonstrated the ability to apply scientific rigour to spatial modelling of aquaculture problems including site suitability, biodiversity, landscape capacity and multi-site particulate dispersion. The various sub-models and their components sub-models can be stand-alone decision-making tools or combined into a holistic model which incorporates a flexible method of trade-off management. The range of GIS-based coastal analytical tools developed form the core of a decision support system that can enable the objective management of the increasing demands on the coastal zone, while having the capacity to bring together stakeholders, multiple agencies and governing bodies that are responsible for management and use of these precious and sometimes threatened resources

    Advances in Robotics, Automation and Control

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    The book presents an excellent overview of the recent developments in the different areas of Robotics, Automation and Control. Through its 24 chapters, this book presents topics related to control and robot design; it also introduces new mathematical tools and techniques devoted to improve the system modeling and control. An important point is the use of rational agents and heuristic techniques to cope with the computational complexity required for controlling complex systems. Through this book, we also find navigation and vision algorithms, automatic handwritten comprehension and speech recognition systems that will be included in the next generation of productive systems developed by man
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