600 resultados para - Generative Fertigungsverfahren


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Motion capture continues to be adopted across a range of creative fields including, animation, games, visual effects, dance, live theatre and the visual arts. This panel will discuss and showcase the use of motion capture across these creative fields and consider the future of virtual production in the creative industries.

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Technical images such as photography, film and video, are dependent on apparatuses for their production and dissemination, yet the apparatus itself is often hidden or obscured in the experience of the work and the discourse that surrounds it. This practice-led research identifies key practice strategies to foreground the apparatus both in the production of work and in its presentation. It therefore develops critical and generative strategies to explore and interrogate the workings of the 'apparatus-audience complex,' and the particular modes of spectatorship that this entails.

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Indirect inference (II) is a methodology for estimating the parameters of an intractable (generative) model on the basis of an alternative parametric (auxiliary) model that is both analytically and computationally easier to deal with. Such an approach has been well explored in the classical literature but has received substantially less attention in the Bayesian paradigm. The purpose of this paper is to compare and contrast a collection of what we call parametric Bayesian indirect inference (pBII) methods. One class of pBII methods uses approximate Bayesian computation (referred to here as ABC II) where the summary statistic is formed on the basis of the auxiliary model, using ideas from II. Another approach proposed in the literature, referred to here as parametric Bayesian indirect likelihood (pBIL), we show to be a fundamentally different approach to ABC II. We devise new theoretical results for pBIL to give extra insights into its behaviour and also its differences with ABC II. Furthermore, we examine in more detail the assumptions required to use each pBII method. The results, insights and comparisons developed in this paper are illustrated on simple examples and two other substantive applications. The first of the substantive examples involves performing inference for complex quantile distributions based on simulated data while the second is for estimating the parameters of a trivariate stochastic process describing the evolution of macroparasites within a host based on real data. We create a novel framework called Bayesian indirect likelihood (BIL) which encompasses pBII as well as general ABC methods so that the connections between the methods can be established.

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This paper presents research that investigated the role of conflict in the editorial process of the online encyclopedia, Wikipedia. The study used a grounded approach to analyzing 147 conversations about quality from the archived history of the Wikipedia article 'Australia'. It found that conflict in Wikipedia is a generative friction, regulated by references to policy as part of a coordinated effort within the community to improve the quality of articles.

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This paper uses theoretical resources from the sociology of education to consider the teaching of sociology in teacher education programs in Australia. Once a disciplinary ‘pillar’ of teacher education, sociology’s contribution has become less explicit while more integrated, with consequences for disciplinary identity. Here we explore how sociology is taught in teacher education curricula on two fronts. Firstly we outline how sociology is embedded as one of a number of competing perspectives in foundational studies, and its pedagogic consequences. Then we consider the powerful contribution of sociology in literacy studies, amidst public debate about literacy performance. The analysis draws on Bernstein’s (2000) distinction between singular disciplinary curriculum design and practically-oriented regional curriculum design. We seek to trouble the commonsense binary between theory and practice that structures debates around professional education in higher education more broadly, and to dignify service sociology as a valuable, generative site for the discipline’s future.

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We advocate for the use of predictive techniques in interactive computer music systems. We suggest that the inclusion of prediction can assist in the design of proactive rather than reactive computational performance partners. We summarize the significant role prediction plays in human musical decisions, and the only modest use of prediction in interactive music systems to date. After describing how we are working toward employing predictive processes in our own metacreation software we reflect on future extensions to these approaches.

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“Made by Motion” is a collaboration between digital artist Paul Van Opdenbosch and performer and choreographer Elise May; a series of studies on captured motion data used to generating experimental visual forms that reverberate in space and time. The project investigates the invisible forces generated by and influencing the movement of a dancer. Along with how the forces can be captured and applied to generating visual outcomes that surpass simple data visualisation, projecting the intent of the performer’s movements. The source or ‘seed’ comes from using an Xsens MVN - Inertial Motion Capture system to capture spontaneous dance movements, with the visual generation conducted through a customised dynamics simulation. In this first series the visual investigation focused on manipulating the movement date at the instance of capture, capture been the recording of three-dimensional movement as ‘seen’ by the hardware and ‘understood’ through the calibration of software. By repositioning the capture hardware on the body we can effectively change how the same sequence of movements is ‘seen’ by the motion capture system thus generating a different visual result from effetely identical movement. The outcomes from the experiments clearly demonstrates the effectiveness of using motion capture hardware as a creative tool to manipulate the perception of the capture subject, in this case been a sequence of dance movements. The creative work exhibited is a cross-section of the experiments conducted in practice with the first animated work (Movement A - Control) using the motion capture hardware in its default ‘normal’ configuration. Following this is the lower body moved to the upper body (Lb-Ub), right arm moved onto the left arm (Ra-La), right leg moved onto the left leg (Rl-Ll) and finally the left leg moved onto a object that is then held in the left hand (Ll-Pf (Lh)).

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My practice-led research explores and maps workflows for generating experimental creative work involving inertia based motion capture technology. Motion capture has often been used as a way to bridge animation and dance resulting in abstracted visuals outcomes. In early works this process was largely done by rotoscoping, reference footage and mechanical forms of motion capture. With the evolution of technology, optical and inertial forms of motion capture are now more accessible and able to accurately capture a larger range of complex movements. Made by Motion is a collaboration between digital artist Paul Van Opdenbosch and performer and choreographer Elise May; a series of studies on captured motion data used to generate experimental visual forms that reverberate in space and time. The project investigates the invisible forces generated by and influencing the movement of a dancer. Along with how the forces can be captured and applied to generating visual outcomes that surpass simple data visualisation, projecting the intent of the performer’s movements. The source or ‘seed’ comes from using an Xsens MVN – Inertial Motion Capture system to capture spontaneous dance movements, with the visual generation conducted through a customised dynamics simulation. In my presentation I will be displaying and discussing a selected creative works from the project along with the process and considerations behind the work.

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This research looked at using the metaphor of biological evolution as a way of solving architectural design problems. Drawing from fields such as language grammars, algorithms and cellular biology, this thesis looked at ways of encoding design information for processing. The aim of this work is to help in the building of software that support the architectural design process and allow designers to examine more variations.

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This chapter begins with a discussion of the economic, political, and social context of the recent global financial crisis, which casts into relief current boundaries of criminology, permeated and made fluid in criminology's recent cultural turn. This cultural turn has reinvigorated criminology, providing new objects of analysis and rich and thick descriptions of the relationship between criminal justice and the conditions of life in ‘late modernity’. Yet in comparison with certain older traditions that sought to articulate criminal justice issues with a wider politics of contestation around political economies and social welfare policies of different polities, many of the current leading culturalist accounts tend in their globalized convergences to produce a strangely decontextualized picture in which we are all subject to the zeitgeist of a unitary ‘late modernity’ which does not differ between, for example, social democratic and neo-liberal polities, let alone allow for the widespread persistence of the pre-modern. It is argued that that contrary to this globalizing trend there are signs within criminology that life is being breathed back into social democratic and penal welfare concerns, habitus, and practices. The chapter discusses three of these signs: the emergence of neo-liberalism as a subject of criminology; a developing comparative penology which recognizes differences in the political economies of capitalist states and evinces a renewed interest in inequality; and a nascent revolt against the ‘generative grammar’, ‘pathological disciplinarities’, and ‘imaginary penalities’ of neoliberal managerialism.

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My practice-led research explores and maps workflows for generating experimental creative work involving inertia based motion capture technology. Motion capture has often been used as a way to bridge animation and dance resulting in abstracted visuals outcomes. In early works this process was largely done by rotoscoping, reference footage and mechanical forms of motion capture. With the evolution of technology, optical and inertial forms of motion capture are now more accessible and able to accurately capture a larger range of complex movements. The creative work titled “Contours in Motion” was the first in a series of studies on captured motion data used to generating experimental visual forms that reverberate in space and time. With the source or ‘seed’ comes from using an Xsens MVN - Inertial Motion Capture system to capture spontaneous dance movements, with the visual generation conducted through a customised dynamics simulation. The aim of the creative work was to diverge way from a standard practice of using particle system and/or a simple re-targeting of the motion data to drive a 3d character as a means to produce abstracted visual forms. To facilitate this divergence a virtual dynamic object was tether to a selection of data points from a captured performance. The proprieties of the dynamic object were then adjusted to balance the influences from the human movement data with the influence of computer based randomization. The resulting outcome was a visual form that surpassed simple data visualization to project the intent of the performer’s movements into a visual shape itself. The reported outcomes from this investigation have contributed to a larger study on the use of motion capture in the generative arts, furthering the understanding of and generating theories on practice.

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There is no doubt that place branding is a powerful and ubiquitous practice deployed around the globe. Parallel to its acceptance and development as a distinct discipline is an understanding that place branding as responsible practice offers the means to achieve widespread economic, social and cultural benefits. Drawing on work around place and identity in cultural geography and cultural studies, this paper engages critically with this vision. Specifically, it challenges the widely-held assumption that the relationship between place branding and place identity is fundamentally reflective, arguing instead that this relationship is inherently generative. This shift in perspective, explored in relation to current responsible place branding practice, is central to the realisation of place branding as a force for good.

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This paper presents a robust place recognition algorithm for mobile robots that can be used for planning and navigation tasks. The proposed framework combines nonlinear dimensionality reduction, nonlinear regression under noise, and Bayesian learning to create consistent probabilistic representations of places from images. These generative models are incrementally learnt from very small training sets and used for multi-class place recognition. Recognition can be performed in near real-time and accounts for complexity such as changes in illumination, occlusions, blurring and moving objects. The algorithm was tested with a mobile robot in indoor and outdoor environments with sequences of 1579 and 3820 images, respectively. This framework has several potential applications such as map building, autonomous navigation, search-rescue tasks and context recognition.

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With specific reference to the writing of Dan Graham and the experiences of creative practice, this paper will elaborate an account of studio practice as a topology - a theory drawn from mathematics in which space is understood not as a static field but in terms of properties of connectedness, movement and differentiation. This paper will trace a brief sequence of topological formulations to draw together the expression of topology as form and its structural dimension as a methodology in the specific context of the author’s studio practice. In so doing, this paper seeks to expand the notion of topology in art beyond its association with Conceptual Art of the 1960s and 70s to propose that topology provides a dynamic theoretical model for apprehending the generative ‘logic’ that gives direction and continuity to the art-making process.

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This paper addresses the problem of determining optimal designs for biological process models with intractable likelihoods, with the goal of parameter inference. The Bayesian approach is to choose a design that maximises the mean of a utility, and the utility is a function of the posterior distribution. Therefore, its estimation requires likelihood evaluations. However, many problems in experimental design involve models with intractable likelihoods, that is, likelihoods that are neither analytic nor can be computed in a reasonable amount of time. We propose a novel solution using indirect inference (II), a well established method in the literature, and the Markov chain Monte Carlo (MCMC) algorithm of Müller et al. (2004). Indirect inference employs an auxiliary model with a tractable likelihood in conjunction with the generative model, the assumed true model of interest, which has an intractable likelihood. Our approach is to estimate a map between the parameters of the generative and auxiliary models, using simulations from the generative model. An II posterior distribution is formed to expedite utility estimation. We also present a modification to the utility that allows the Müller algorithm to sample from a substantially sharpened utility surface, with little computational effort. Unlike competing methods, the II approach can handle complex design problems for models with intractable likelihoods on a continuous design space, with possible extension to many observations. The methodology is demonstrated using two stochastic models; a simple tractable death process used to validate the approach, and a motivating stochastic model for the population evolution of macroparasites.