The silence of objects : forming the unsayable

The silence of objects phenomenologically explores the experience and memory of trauma through object-based artwork. It springs from a desire to map difficult psychological terrain and does so by tracking the process of a coming into 'expression' to communicate notions of loss, detachment and powerlessness. It maps a journey from silence to a forming 'voice' that gives shape to the unsayable. This practice-led research is multifaceted. Whilst the creative element uses transformed objects as material metaphors to tap into the sensory and affective operations of art, the written component blends reflection with theory and is informed by art theorists Jill Bennett and Mignon Nixon. By establishing a dialogue between theoretical constructs and creative works I consider how giving form to deep consciousness can counter the effects of trauma manifest as silence and invisibility.

The naturally imperfect form : investigations of the application of digital sculpting methods - extracted art : incorporating and translating ‘found art’ into the medium of digital sculpture

This dissertation analyses how physical objects are translated into digital artworks using techniques which can lead to ‘imperfections’ in the resulting digital artwork that are typically removed to arrive at a ‘perfect’ final representation. The dissertation discusses the adaptation of existing techniques into an artistic workflow that acknowledges and incorporates the imperfections of translation into the final pieces. It presents an exploration of the relationship between physical and digital artefacts and the processes used to move between the two. The work explores the 'craft' of digital sculpting and the technology used in producing what the artist terms ‘a naturally imperfect form’, incorporating knowledge of traditional sculpture, an understanding of anatomy and an interest in the study of bones (Osteology). The outcomes of the research are presented as a series of digital sculptural works, exhibited as a collection of curiosities in multiple mediums, including interactive game spaces, augmented reality (AR), rapid prototype prints (RP) and video displays.

The paradox of autistic art

Certain autistic children whose linguistic ability is virtually nonexistent can draw natural scenes from memory with astonishing accuracy. In particular their drawings display convincing perspective. In contrast, normal children of the same preschool age group and even untrained adults draw primitive schematics or symbols of objects which they can verbally identify. These are usually conceptual outlines devoid of detail. It is argued that the difference between autistic child artists and normal individuals is that autistic artists make no assumptions about what is to be seen in their environment. They have not formed mental representations of what is significant and consequently perceive all details as equally important. Equivalently, they do not impose visual or linguistic schema -- a process necessary for rapid conceptualisation in a dynamic existence, especially when the information presented to the eye is incomplete.

The ways of things: Objects in the studio

Conventions of the studio presuppose the artist as the active agent, imposing his/her will upon and through objects that remain essentially inert. However, this characterisation of practice overlooks the complex object dynamics that underpin the art-making process. Far from passive entities, objects are resistant, ‘speaking back’ to the artist, impressing their will upon their surroundings. Objects stick to one another, fall over, drip, spill, spatter and chip one another. Objects support, dismantle, cover and transform one another. Objects are both the apparatus of the studio and its products. It can be argued that the work of art is as much shaped by objects as it is by human impulse. Within this alternate ontology, the artist becomes but one element in a constellation of objects. Drawing upon Graham Harman’s Object-Oriented Ontology and a selection of photographs of my studio processes, this practice-led paper will explore the notion of agentive objects and the ways in which the contemporary art studio can be reconsidered as a primary site for the production of new object relationships.

Focus on Form : J. J. Tikkanen, Giotto and Art Research in the 19th Century

My doctoral dissertation is on Johan Jakob Tikkanen (1857 1930), the first professor of art history in Finland, and his significance and methods in the context of late 19th and early 20th-century European art history. Tikkanen was one of the pioneering scholars in the field of medieval art research, and, along with Anton Springer, Heinrich Wölfflin, Aloïs Riegl, Adolfo Venturi, Franz Wickhoff, Julius von Schlosser, Aby Warburg, Emile Mâle and others, one of the scholars who defined art history as an independent academic discipline. Tikkanen s scholarly interests and his methods resemble those of many formalistically oriented German and Austrian art historians of his time. He became well known throughout Europe, mainly for his studies on illustrated medieval manuscripts. Tikkanen s dissertation, Der Malerische Styl Giotto s Versuch zu einer Characteristik Desselben, from 1884 was regarded in its day as the best form-analytical study on the painter. It has a central position in the present thesis, as it already included nearly all the methods that Tikkanen used and elaborated upon throughout his career. Giotto also gives a good perspective for comparing Tikkanen s ideas with a long art-historical tradition. Tikkanen was profoundly interested in artistic creativity. In his own words, he wanted to study das künstlerische Können , artistic ability, instead of das künstlerische Wollen or artistic will, which was an important theoretical issue in art history in the late 19th century. This starting point led him to the history of style and iconographical research. Along with the Danish art historian, Julius Lange, he was one of the first scholars who began to study the meaning of gestures and postures in art. In my dissertation I have emphasized the importance of Tikkanen s personal art education. I regard it as having influenced both his scholarly argumentation and his working methods. I have also written a short overview of the situation of art history in Finland and in Northern Countries before Tikkanen s time in order to give an idea of his scientific background. My thesis is a critical and historiographical study on J. J. Tikkanen s role in the development of art history and its methodology.

Constructing a wire-frame from views on arbitrary view planes for objects with conic sections inclined to all view planes

A new and efficient approach to construct a 3D wire-frame of an object from its orthographic projections is described. The input projections can be two or more and can include regular and complete auxiliary views. Each view may contain linear, circular and other conic sections. The output is a 3D wire-frame that is consistent with the input views. The approach can handle auxiliary views containing curved edges. This generality derives from a new technique to construct 3D vertices from the input 2D vertices (as opposed to matching coordinates that is prevalent in current art). 3D vertices are constructed by projecting the 2D vertices in a pair of views on the common line of the two views. The construction of 3D edges also does not require the addition of silhouette and tangential vertices and subsequently splitting edges in the views. The concepts of complete edges and n-tuples are introduced to obviate this need. Entities corresponding to the 3D edge in each view are first identified and the 3D edges are then constructed from the information available with the matching 2D edges. This allows the algorithm to handle conic sections that are not parallel to any of the viewing directions. The localization of effort in constructing 3D edges is the source of efficiency of the construction algorithm as it does not process all potential 3D edges. Working of the algorithm on typical drawings is illustrated. (C) 2011 Elsevier Ltd. All rights reserved.

De la lírica medieval a la moderna : tradicionalidad e individualidad en la poesía española

Integran este número de la revista ponencias presentadas en Studia Hispanica Medievalia VIII : Actas de las X Jornadas Internacionales de Literatura Española Medieval, 2011, y de Homenaje al Quinto Centenario del Cancionero General de Hernando del Castillo.

La civilización vasca medieval: vida(s), cotidiana(s), mentalidad(es) y cultura(s)

[ES]A lo largo de las páginas de este trabajo se pasa revista a diversas cuestiones que permiten realizar una aproximación a las diversas formas de vida cotidiana y mentalidad del País Vasco y Navarra durante los siglos bajomedievales. Esas cuestiones aluden al primum vivere, al ciclo vital, al control de la vida privada de los individuos y pública de las comunidades por parte de las autoridades, las fiestas, las supersticiones y distintos aspectos relativos a la cultura, como literatura, historiografía y arte.

Os cavaleiros imaginários de Terry Gilliam: uma análise da transição da figura do cavaleiro medieval da literatura para o cinema

As narrativas em torno da busca do Graal tiveram origem no século XI e foram de grande importância para fixar a imagem de um personagem típico da sociedade medieval, o cavaleiro, como um novo modelo heroico. Nesse sentido, os cavaleiros que encontraram o Graal nessas narrativas, especialmente no ciclo literário conhecido como Matéria da Bretanha, representam a configuração máxima desse paradigma. Esta pesquisa visa analisar a permanência de tal imagem no cinema, que é igualmente uma arte narrativa, como o eram as novelas de cavalaria que originaram o modelo. O corpus a ser analisado são três significativas obras do cineasta norte-americano Terry Gilliam que direta ou indiretamente retomam a questão do Graal: Monty Python em busca do Cálice sagrado (Monty Phyton and The Holy Grail, 1974), O pescador de ilusões (The Fisher King, 1991) e Os doze macacos (Twelve Monkeys, 1995). Assim, procura-se com esta tese traçar um panorama das retomadas da imagem literária e medieval dos cavaleiros no cinema, assim como observar as mudanças no padrão dessas imagens descritas literariamente para sua representação óptico-sonora

Layered Graphical Models for Tracking Partially-Occluded Objects

Partial occlusions are commonplace in a variety of real world computer vision applications: surveillance, intelligent environments, assistive robotics, autonomous navigation, etc. While occlusion handling methods have been proposed, most methods tend to break down when confronted with numerous occluders in a scene. In this paper, a layered image-plane representation for tracking people through substantial occlusions is proposed. An image-plane representation of motion around an object is associated with a pre-computed graphical model, which can be instantiated efficiently during online tracking. A global state and observation space is obtained by linking transitions between layers. A Reversible Jump Markov Chain Monte Carlo approach is used to infer the number of people and track them online. The method outperforms two state-of-the-art methods for tracking over extended occlusions, given videos of a parking lot with numerous vehicles and a laboratory with many desks and workstations.

ART-EMAP: A Neural Network Architecture for Learning and Prediction by Evidence Accumulation

This paper introduces ART-EMAP, a neural architecture that uses spatial and temporal evidence accumulation to extend the capabilities of fuzzy ARTMAP. ART-EMAP combines supervised and unsupervised learning and a medium-term memory process to accomplish stable pattern category recognition in a noisy input environment. The ART-EMAP system features (i) distributed pattern registration at a view category field; (ii) a decision criterion for mapping between view and object categories which can delay categorization of ambiguous objects and trigger an evidence accumulation process when faced with a low confidence prediction; (iii) a process that accumulates evidence at a medium-term memory (MTM) field; and (iv) an unsupervised learning algorithm to fine-tune performance after a limited initial period of supervised network training. ART-EMAP dynamics are illustrated with a benchmark simulation example. Applications include 3-D object recognition from a series of ambiguous 2-D views.

ART-EMAP: A Neural Network Architecture for Object Recognition by Evidence Accumulation

A new neural network architecture is introduced for the recognition of pattern classes after supervised and unsupervised learning. Applications include spatio-temporal image understanding and prediction and 3-D object recognition from a series of ambiguous 2-D views. The architecture, called ART-EMAP, achieves a synthesis of adaptive resonance theory (ART) and spatial and temporal evidence integration for dynamic predictive mapping (EMAP). ART-EMAP extends the capabilities of fuzzy ARTMAP in four incremental stages. Stage 1 introduces distributed pattern representation at a view category field. Stage 2 adds a decision criterion to the mapping between view and object categories, delaying identification of ambiguous objects when faced with a low confidence prediction. Stage 3 augments the system with a field where evidence accumulates in medium-term memory (MTM). Stage 4 adds an unsupervised learning process to fine-tune performance after the limited initial period of supervised network training. Each ART-EMAP stage is illustrated with a benchmark simulation example, using both noisy and noise-free data. A concluding set of simulations demonstrate ART-EMAP performance on a difficult 3-D object recognition problem.

Fast Learning VIEWNET Architectures for Recognizing 3-D Objects from Multiple 2-D Views

The recognition of 3-D objects from sequences of their 2-D views is modeled by a family of self-organizing neural architectures, called VIEWNET, that use View Information Encoded With NETworks. VIEWNET incorporates a preprocessor that generates a compressed but 2-D invariant representation of an image, a supervised incremental learning system that classifies the preprocessed representations into 2-D view categories whose outputs arc combined into 3-D invariant object categories, and a working memory that makes a 3-D object prediction by accumulating evidence from 3-D object category nodes as multiple 2-D views are experienced. The simplest VIEWNET achieves high recognition scores without the need to explicitly code the temporal order of 2-D views in working memory. Working memories are also discussed that save memory resources by implicitly coding temporal order in terms of the relative activity of 2-D view category nodes, rather than as explicit 2-D view transitions. Variants of the VIEWNET architecture may also be used for scene understanding by using a preprocessor and classifier that can determine both What objects are in a scene and Where they are located. The present VIEWNET preprocessor includes the CORT-X 2 filter, which discounts the illuminant, regularizes and completes figural boundaries, and suppresses image noise. This boundary segmentation is rendered invariant under 2-D translation, rotation, and dilation by use of a log-polar transform. The invariant spectra undergo Gaussian coarse coding to further reduce noise and 3-D foreshortening effects, and to increase generalization. These compressed codes are input into the classifier, a supervised learning system based on the fuzzy ARTMAP algorithm. Fuzzy ARTMAP learns 2-D view categories that are invariant under 2-D image translation, rotation, and dilation as well as 3-D image transformations that do not cause a predictive error. Evidence from sequence of 2-D view categories converges at 3-D object nodes that generate a response invariant under changes of 2-D view. These 3-D object nodes input to a working memory that accumulates evidence over time to improve object recognition. ln the simplest working memory, each occurrence (nonoccurrence) of a 2-D view category increases (decreases) the corresponding node's activity in working memory. The maximally active node is used to predict the 3-D object. Recognition is studied with noisy and clean image using slow and fast learning. Slow learning at the fuzzy ARTMAP map field is adapted to learn the conditional probability of the 3-D object given the selected 2-D view category. VIEWNET is demonstrated on an MIT Lincoln Laboratory database of l28x128 2-D views of aircraft with and without additive noise. A recognition rate of up to 90% is achieved with one 2-D view and of up to 98.5% correct with three 2-D views. The properties of 2-D view and 3-D object category nodes are compared with those of cells in monkey inferotemporal cortex.

3-D Object Recognition by the ART-EMAP Evidence Accumulation Network

ART-EMAP synthesizes adaptive resonance theory (AHT) and spatial and temporal evidence integration for dynamic predictive mapping (EMAP). The network extends the capabilities of fuzzy ARTMAP in four incremental stages. Stage I introduces distributed pattern representation at a view category field. Stage 2 adds a decision criterion to the mapping between view and object categories, delaying identification of ambiguous objects when faced with a low confidence prediction. Stage 3 augments the system with a field where evidence accumulates in medium-term memory (MTM). Stage 4 adds an unsupervised learning process to fine-tune performance after the limited initial period of supervised network training. Simulations of the four ART-EMAP stages demonstrate performance on a difficult 3-D object recognition problem.