Segmentation of scenes of mobile objects and demonstrable backgrounds

In this paper we present a real-time foreground–background segmentation algorithm that exploits the following observation (very often satisfied by a static camera positioned high in its environment). If a blob moves on a pixel p that had not changed its colour significantly for a few frames, then p was probably part of the background when its colour was static. With this information we are able to update differentially pixels believed to be background. This work is relevant to autonomous minirobots, as they often navigate in buildings where smart surveillance cameras could communicate wirelessly with them. A by-product of the proposed system is a mask of the image regions which are demonstrably background. Statistically significant tests show that the proposed method has a better precision and recall rates than the state of the art foreground/background segmentation algorithm of the OpenCV computer vision library.

Art unions legislation in Queensland

In Queensland, the legislation governing the conduct of art unions such as bingo, raffles and lucky envelopes is the Art Unions Act 1992 (ΑAct≅). The Act is administered by the Queensland Office of Gaming Regulation (ΑQOGR≅) which is part of the Queensland Treasury portfolio. The Act and other legislation such as the Criminal Code, Vagrants Gaming and Other Offences Act, generally makes it unlawful for a person to conduct art unions unless they are authorised to do so. The Art Unions Act allows Αeligible≅ nonprofit associations such as charities, schools, sporting and community groups to raise funds for their stated objects. Art unions were legalised in the early part of this century primarily to assist charities and other approved associations to raise funds for worthwhile causes. This principle is continued in the 1992 Act. The Queensland art union industry had a turnover of over$190M in 1996/97 and our Queensland art unions continue to attract not just sales from Queensland residents but also interstate and overseas buyers. Art unions continue to be an attractive form of fundraising for many nonprofit associations.

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.

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.

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.

Art, adolescence and Social Work: Anja, the invisible manager

This article has been written with the intention of being able to analyse the contributions of art —theatre, in this case— to the practice of social work. For this purpose, we have chosen to read the social reality in which we intervene through the lens of social constructionism. This helps us to rescue the social and subjective side of art, and, moreover, to recover the depathologization of the subject in professional intervention. Thus, using a practical case taken from work with adolescents in the German FSJ programme, hand-in-hand with a young girl called Anja we trace the developmental and sociological aspects of adolescence in order to later address certain common points of art and psychosocial work. Art will hence be redefined as a transitional object allowing questions to be addressed relating to (self-) perception, attachment, communication and changes in conduct as the ultimate goal of professional action. Lastly, we note the limitations and risks of art-based intervention, in order to conclude with a final synopsis.

About infamy: the filthiness of Art and its diogenic disease

In this paper, we postulate the direct relationship that exists between waste production and artistic objects; its manufacturing system, consumption, and subsequent waste. What arises in this relationship then, is another character of interest –and that will serve as a reference to compare its modus operandi with the place of artists and the arts–, in this sick world, the Diogenes. The obsessed that lives among the garbage. The absurdity of the conquest of the infinite of the illogical within the logical. The amount clouded and blinded, nothing is enjoyed, nothing is appreciated; the countless abandons its place in the memory –memorable– and there only exists a pathological accumulation, mountains of garbage, desires to hold on to vital faith of the belief of doing Something for themselves. Working just to work and building something that will not last, like a sand castle, accumulation of detritus and dust. A new logic is born, the enjoyment of diseases and emptiness, the destruction of a world without a history. «Artists of the world, abandon! You have nothing to lose but your own professions!» (Kaprow, 2007, p. 37).