A biologically plausible system for detecting saliency in video

Neuroscientists and cognitive scientists credit the dorsal and ventral pathways for the capability of detecting both still salient and motion salient objects. In this work, a framework is developed to explore potential models of still and motion saliency and is an extension of the original VENUS system. The early visual pathway is modeled by using Independent Component Analysis to learn a set of Gabor-like receptive fields similar to those found in the mammalian visual pathway. These spatial receptive fields form a set of 2D basis feature matrices, which are used to decompose complex visual stimuli into their spatial components. A still saliency map is formed by combining the outputs of convoluting the learned spatial receptive fields with the input stimuli. The dorsal pathway is primarily focused on motion-based information. In this framework, the model uses simple motion segmentation and tracking algorithms to create a statistical model of the motion and color-related information in video streams. A key feature of the human visual system is the ability to detect novelty. This framework uses a set of Gaussian distributions to model color and motion. When a unique event is detected, Gaussian distributions are created and the event is declared novel. The next time a similar event is detected the framework is able to determine that the event is not novel based on the previously created distributions. A forgetting term is also included that allows events that have not been detected for a long period of time to be forgotten

Processpatching: defining new methods in aRt&D

In the context of a rapidly changing domain of contemporary electronic art practice- where the speed of technological innovation and the topicality of art 'process as research' methods are both under constant revision- the process of collaboration between art, computer science and engineering is an important addition to existing 'R&D'. Scholarly as well as practical exploration of artistic methods, viewed in relation to the field of new technology, can be seen to enable and foster innovation in both the conceptualisation and practice of the electronic arts. At the same time, citing new media art in the context of technological innovation brings a mix of scientific and engineering issues to the fore and thereby demands an extended functionality that may lead to R&D, as technology attempts to take account of aesthetic and social considerations in its re-development. This new field of new media or electronic art R&D is different from research and development aimed at practical applications of new technologies as we see them in everyday life. A next step for Research and Development in Art (aRt&D) is a formalisation of the associated work methods, as an essential ingredient for interdisciplinary collaboration. This study investigates how electronic art patches together processes and methods from the arts, engineering and computer science environments. It provides a framework describing the electronic art methods to improve collaboration by informing others about one's artistic research and development approach. This investigation is positioned in the electronic art laboratory where new alliances with other disciplines are established. It provides information about the practical and theoretical aspects of the research and development processes of artists. The investigation addresses fundamental questions about the 'research and development methods' (discussed and defined at length in these pages), of artists who are involved in interdisciplinary collaborations amongst and between the fields of Art, Computer Science, and Engineering. The breadth of the fields studied necessarily forced a tight focus on specific issues in the literature, addressed herein through a series of focused case studies which demonstrate the points of synergy and divergence between the fields of artistic research and development, in a wider art&D' context. The artistic methods proposed in this research include references from a broad set of fields (e. g. Technology, Media Arts, Theatre and Performance, Systems Theories, the Humanities, and Design Practice) relevant to and intrinsically intertwined with this project and its placement in an interdisciplinary knowledge domain. The aRt&D Matrix provides a complete overview of the observed research and development methods in electronic arts, including references to related disciplines and methods from other fields. The new Matrix developed and offered in this thesis also provides an instrument for analysing the interdisciplinary collaboration process that exclusively reflects the information we need for the overview of the team constellation. The tool is used to inform the collaborators about the backgrounds of the other participants and thus about the expected methods and approaches. It provides a map of the bodies of knowledge and expertise represented in any given cross-disciplinary team, and thus aims to lay the groundwork for a future aRt&D framework of use to future scholars and practitioners alike

New Methods Visualizing Mesostructured Materials

On the one hand this work intends to present new possibilities on how the combination of characterization methods can be used to gain information not available from the individual techniques. On the other hand discrete tomography - a relatively new method in materials science - is used to image real three-dimensional nano structures with a resolution of only a few nanometers. Visualization not only facilitates the interpretation of scientific results, but also aims at contributing to a better general understanding of nano technology

Reconciling Predictive Coding and Biased Competition Models of Cortical Function

A simple variation of the standard biased competition model is shown, via some trivial mathematical manipulations, to be identical to predictive coding. Specifically, it is shown that a particular implementation of the biased competition model, in which nodes compete via inhibition that targets the inputs to a cortical region, is mathematically equivalent to the linear predictive coding model. This observation demonstrates that these two important and influential rival theories of cortical function are minor variations on the same underlying mathematical model

The emergence of active perception - seeking conceptual foundations

The aim of this thesis is to explain the emergence of active perception. It takes an interdisciplinary approach, by providing the necessary conceptual foundations for active perception research - the key notions that bridge the conceptual gaps remaining in understanding emergent behaviours of active perception in the context of robotic implementations. On the one hand, the autonomous agent approach to mobile robotics claims that perception is active. On the other hand, while explanations of emergence have been extensively pursued in Artificial Life, these explanations have not yet successfully accounted for active perception.The main question dealt with in this thesis is how active perception systems, as behaviour -based autonomous systems, are capable of providing relatively optimal perceptual guidance in response to environmental challenges, which are somewhat unpredictable. The answer is: task -level emergence on grounds of complicatedly combined computational strategies, but this notion needs further explanation.To study the computational strategies undertaken in active perception re- search, the thesis surveys twelve implementations. On the basis of the surveyed implementations, discussions in this thesis show that the perceptual task executed in support of bodily actions does not arise from the intentionality of a homuncu- lus, but is identified automatically on the basis of the dynamic small mod- ules of particular robotic architectures. The identified tasks are accomplished by quasi -functional modules and quasi- action modules, which maintain transformations of perceptual inputs, compute critical variables, and provide guidance of sensory -motor movements to the most relevant positions for fetching further needed information. Given the nature of these modules, active perception emerges in a different fashion from the global behaviour seen in other autonomous agent research.The quasi- functional modules and quasi- action modules cooperate by estimating the internal cohesion of various sources of information in support of the envisaged task. Specifically, such modules basically reflect various computational facilities for a species to single out the most important characteristics of its ecological niche. These facilities help to achieve internal cohesion, by maintaining a stepwise evaluation over the previously computed information, the required task, and the most relevant features presented in the environment.Apart from the above exposition of active perception, the process of task - level emergence is understood with certain principles extracted from four models of life origin. First, the fundamental structure of active perception is identified as the stepwise computation. Second, stepwise computation is promoted from baseline to elaborate patterns, i.e. from a simple system to a combinatory system. Third, a core requirement for all stepwise computational processes is the comparison between collected and needed information in order to insure the contribution to the required task. Interestingly, this point indicates that active perception has an inherent pragmatist dimension.The understanding of emergence in the present thesis goes beyond the distinc- tion between external processes and internal representations, which some current philosophers argue is required to explain emergence. The additional factors are links of various knowledge sources, in which the role of conceptual foundations is two -fold. On the one hand, those conceptual foundations elucidate how various knowledge sources can be linked. On the other, they make possible an interdisci- plinary view of emergence. Given this two -fold role, this thesis shows the unity of task -level emergence. Thus, the thesis demonstrates a cooperation between sci- ence and philosophy for the purpose of understanding the integrity of emergent cognitive phenomena

A feedback model of perceptual learning and categorisation

Top-down, feedback, influences are known to have significant effects on visual information processing. Such influences are also likely to affect perceptual learning. This article employs a computational model of the cortical region interactions underlying visual perception to investigate possible influences of top-down information on learning. The results suggest that feedback could bias the way in which perceptual stimuli are categorised and could also facilitate the learning of sub-ordinate level representations suitable for object identification and perceptual expertise

Mobile Robots

The objective of this book is to cover advances of mobile robotics and related technologies applied for multi robot systems' design and development. Design of control system is a complex issue, requiring the application of information technologies to link the robots into a single network. Human robot interface becomes a demanding task, especially when we try to use sophisticated methods for brain signal processing. Generated electrophysiological signals can be used to command different devices, such as cars, wheelchair or even video games. A number of developments in navigation and path planning, including parallel programming, can be observed. Cooperative path planning, formation control of multi robotic agents, communication and distance measurement between agents are shown. Training of the mobile robot operators is very difficult task also because of several factors related to different task execution. The presented improvement is related to environment model generation based on autonomous mobile robot observations