Point-based Medialness for Animal and Plant Identification

Abstract We introduce the idea of using a perception-based medial point description [#kovacs1998medial] of a natural form (2D static or in movement) as a framework for a part-based shape representation which can then be efficiently used in biological species identification and matching tasks. The first step is one of fuzzy medialness measurements of 2D segmented objects from intensity images which emphasises main shape information characteristics of an object's parts (e.g. concavities and folds along a contour). We distinguish interior from exterior shape description. Interior medialness is used to characterise deformations from straightness, corners and necks, while exterior medialness identifies the main concavities and inlands which are useful to verify parts extent and reason about articulation and movement. In a second step we identify a set of characteristic features points built from three types. We define (i) an Interior dominant point as a well localised peak value in medialness representation, while (ii) an exterior dominant point is evaluated by identifying a region of concavity sub-tended by a minimum angular support. Furthermore, (iii) convex point are extracted from the form to further characterise the elongation of parts. Our evaluated feature points, together are sufficiently invariant to shape movement, where the articulation in moving objects are characterised by exterior dominant points. In the third step, a robust shape matching algorithm is designed that finds the most relevant targets from a database of templates by comparing the dominant feature points in a scale, rotation and translation invariant way (inspired by the SIFT method [#lowe2004distinctive]). The performance of our method has been tested on several databases. The robustness of the algorithm is further tested by perturbing the data-set at different scales

Point-based Medialness for Animal and Plant Identification

We introduce the idea of using a perception-based medial point description [9] of a natural form (2D static or in movement) as a framework for a part-based shape representation which can then be efficiently used in biological species identification and matching tasks. The first step is one of fuzzy medialness measurements of 2D segmented objects from intensity images which emphasises main shape information characteristics of an object’s parts (e.g. concavities and folds along a contour). We distinguish interior from exterior shape description. Interior medialness is used to characterise deformations from straightness, corners and necks, while exterior medialness identifies the main concavities and inlands which are useful to verify parts extent and reason about articulation and movement. In a second step we identify a set of characteristic features points built from three types. We define (i) an Interior dominant point as a well localised peak value in medialness representation, while (ii) an exterior dominant point is evaluated by identifying a region of concavity sub-tended by a minimum angular support. Furthermore, (iii) convex point are extracted from the form to further characterise the elongation of parts. Our evaluated feature points, together are sufficiently invariant to shape move ment, where the articulation in moving objects are characterised by exterior dominant points. In the third step, a robust shape matching algorithm is designed that finds the most relevant targets from a database of templates by comparing the dominant feature points in a scale, rotation and translation invariant way (inspired by the SIFT method [17]). The performance of our method has been tested on several databases. The robustness of the algorithm is further tested by perturbing the data-set at different scales

Point-based medialness for 2D shape description and identification

Abstract We propose a perception-based medial point description of a natural form (2D: static or in articulated movement) as a framework for a shape representation which can then be efficiently used in biological species identification and matching tasks. Medialness is defined by adapting and refining a definition first proposed in the cognitive science literature when studying the visual attention of human subjects presented with articulated biological 2D forms in movement, such as horses, dogs and humans (walking, running). In particular, special loci of high medialness for the interior of a form in movement, referred to as “hot spots”, prove most attractive to the human perceptual system. We propose an algorithmic process to identify such hot spots. In this article we distinguish exterior from interior shape representation. We further augment hot spots with extremities of medialness ridges identifying significant concavities (from outside) and convexities (from inside). Our representation is strongly footed in results from cognitive psychology, but also inspired by know-how in art and animation, and the algorithmic part is influenced by techniques from more traditional computer vision. A robust shape matching algorithm is designed that finds the most relevant targets from a database of templates by comparing feature points in a scale, rotation and translation invariant way. The performance of our method has been tested on several databases. The robustness of the algorithm is further tested by perturbing the data-set at different levels

Medialness and the Perception of Visual Art

In this article we explore the practical use of medialness informed by perception studies as a representation and processing layer for describing a class of works of visual art. Our focus is towards the description of 2D objects in visual art, such as found in drawings, paintings, calligraphy, graffiti writing, where approximate boundaries or lines delimit regions associated to recognizable objects or their constitutive parts. We motivate this exploration on the one hand by considering how ideas emerging from the visual arts, cartoon animation and general drawing practice point towards the likely importance of medialness in guiding the interaction of the traditionally trained artist with the artifact. On the other hand, we also consider recent studies and results in cognitive science which point in similar directions in emphasizing the likely importance of medialness, an extension of the abstract mathematical representation known as ‘medial axis’ or ‘Voronoi graphs’, as a core feature used by humans in perceiving shapes in static or dynamic scenarios.We illustrate the use of medialness in computations performed with finished artworks as well as artworks in the process of being created, modified, or evolved through iterations. Such computations may be used to guide an artificial arm in duplicating the human creative performance or used to study in greater depth the finished artworks. Our implementations represent a prototyping of such applications of computing to art analysis and creation and remain exploratory. Our method also provides a possible framework to compare similar artworks or to study iterations in the process of producing a final preferred depiction, as selected by the artist

GRADIENT-ORIENTED BOUNDARY PROFILES FOR SHAPE ANALYSIS USING MEDIAL FEATURES

Gradient-oriented boundary profiles have been developed as a novel method to parameterize boundaries. Boundary profiles are created at locations of high gradient magnitude by averaging intensity within a neighborhood of voxels oriented along the image gradient, making them rotationally invariant and relatively insensitive to image noise. A cumulative Gaussian is fit to the collection of averaged voxel intensities yielding estimates of (1) extrapolated intensity values for voxels located far inside and outside of a boundary and (2) anatomical boundary location. Intrinsic measures of confidence have been developed to eliminate low-confidence parameter estimates. Thresholds placed on these measures of confidence allow for high-confidence unsupervised classification of boundaries. The validity of gradient-oriented profiles is demonstrated on artificially generated three-dimensional test data and shown to accurately parameterize and classify the boundary. Applying the measures of confidence and establishing thresholds, the accuracy of boundary location and intensities estimates improved drastically, making them a high-quality replacement for simpler methods of boundary detection. Towards shape analysis, gradient-oriented boundary profiles are applied to an existing a medial-based approach to shape analysis, known as core atoms. Core atoms in their previous implementation were based on simple gradient direction and unable to form without a priori knowledge of object intensity relative to background. Boundary profiles were applied to core atoms permitting the formation of so called "core profiles". Core profiles remove any restriction on the object's or the background's intensity, allowing multiple objects of differing intensities to be located with a single application.Core profiles were applied to 3D computer-generated data, as well as RT3D ultrasound cardiac phantom data. It was shown on computer-generated data that calculating the volume with core profiles is more accurate then calculating the volume with core atoms, because of the improved accuracy of the boundary location. Two new methods of automatically measuring volume on non-parametric data with core profiles are proposed. Future work with includes constructing medial node models improved by gradient-oriented boundary profiles for automated left ventricular identification and measurement

Across Space and Time. Papers from the 41st Conference on Computer Applications and Quantitative Methods in Archaeology, Perth, 25-28 March 2013

This volume presents a selection of the best papers presented at the forty-first annual Conference on Computer Applications and Quantitative Methods in Archaeology. The theme for the conference was "Across Space and Time", and the papers explore a multitude of topics related to that concept, including databases, the semantic Web, geographical information systems, data collection and management, and more

Across Space and Time Papers from the 41st Conference on Computer Applications and Quantitative Methods in Archaeology, Perth, 25-28 March 2013

The present volume includes 50 selected peer-reviewed papers presented at the 41st Computer Applications and Quantitative Methods in Archaeology Across Space and Time (CAA2013) conference held in Perth (Western Australia) in March 2013 at the University Club of Western Australia and hosted by the recently established CAA Australia National Chapter. It also hosts a paper presented at the 40th Computer Applications and Quantitative Methods in Archaeology (CAA2012) conference held in Southampton

Analysis of physiological signals using machine learning methods

Technological advances in data collection enable scientists to suggest novel approaches, such as Machine Learning algorithms, to process and make sense of this information. However, during this process of collection, data loss and damage can occur for reasons such as faulty device sensors or miscommunication. In the context of time-series data such as multi-channel bio-signals, there is a possibility of losing a whole channel. In such cases, existing research suggests imputing the missing parts when the majority of data is available. One way of understanding and classifying complex signals is by using deep neural networks. The hyper-parameters of such models have been optimised using the process of back propagation. Over time, improvements have been suggested to enhance this algorithm. However, an essential drawback of the back propagation can be the sensitivity to noisy data. This thesis proposes two novel approaches to address the missing data challenge and back propagation drawbacks: First, suggesting a gradient-free model in order to discover the optimal hyper-parameters of a deep neural network. The complexity of deep networks and high-dimensional optimisation parameters presents challenges to find a suitable network structure and hyper-parameter configuration. This thesis proposes the use of a minimalist swarm optimiser, Dispersive Flies Optimisation(DFO), to enable the selected model to achieve better results in comparison with the traditional back propagation algorithm in certain conditions such as limited number of training samples. The DFO algorithm offers a robust search process for finding and determining the hyper-parameter configurations. Second, imputing whole missing bio-signals within a multi-channel sample. This approach comprises two experiments, namely the two-signal and five-signal imputation models. The first experiment attempts to implement and evaluate the performance of a model mapping bio-signals from A toB and vice versa. Conceptually, this is an extension to transfer learning using CycleGenerative Adversarial Networks (CycleGANs). The second experiment attempts to suggest a mechanism imputing missing signals in instances where multiple data channels are available for each sample. The capability to map to a target signal through multiple source domains achieves a more accurate estimate for the target domain. The results of the experiments performed indicate that in certain circumstances, such as having a limited number of samples, finding the optimal hyper-parameters of a neural network using gradient-free algorithms outperforms traditional gradient-based algorithms, leading to more accurate classification results. In addition, Generative Adversarial Networks could be used to impute the missing data channels in multi-channel bio-signals, and the generated data used for further analysis and classification tasks

Políticas de Copyright de Publicações Científicas em Repositórios Institucionais: O Caso do INESC TEC

A progressiva transformação das práticas científicas, impulsionada pelo desenvolvimento das novas Tecnologias de Informação e Comunicação (TIC), têm possibilitado aumentar o acesso à informação, caminhando gradualmente para uma abertura do ciclo de pesquisa. Isto permitirá resolver a longo prazo uma adversidade que se tem colocado aos investigadores, que passa pela existência de barreiras que limitam as condições de acesso, sejam estas geográficas ou financeiras. Apesar da produção científica ser dominada, maioritariamente, por grandes editoras comerciais, estando sujeita às regras por estas impostas, o Movimento do Acesso Aberto cuja primeira declaração pública, a Declaração de Budapeste (BOAI), é de 2002, vem propor alterações significativas que beneficiam os autores e os leitores. Este Movimento vem a ganhar importância em Portugal desde 2003, com a constituição do primeiro repositório institucional a nível nacional. Os repositórios institucionais surgiram como uma ferramenta de divulgação da produção científica de uma instituição, com o intuito de permitir abrir aos resultados da investigação, quer antes da publicação e do próprio processo de arbitragem (preprint), quer depois (postprint), e, consequentemente, aumentar a visibilidade do trabalho desenvolvido por um investigador e a respetiva instituição. O estudo apresentado, que passou por uma análise das políticas de copyright das publicações científicas mais relevantes do INESC TEC, permitiu não só perceber que as editoras adotam cada vez mais políticas que possibilitam o auto-arquivo das publicações em repositórios institucionais, como também que existe todo um trabalho de sensibilização a percorrer, não só para os investigadores, como para a instituição e toda a sociedade. A produção de um conjunto de recomendações, que passam pela implementação de uma política institucional que incentive o auto-arquivo das publicações desenvolvidas no âmbito institucional no repositório, serve como mote para uma maior valorização da produção científica do INESC TEC.The progressive transformation of scientific practices, driven by the development of new Information and Communication Technologies (ICT), which made it possible to increase access to information, gradually moving towards an opening of the research cycle. This opening makes it possible to resolve, in the long term, the adversity that has been placed on researchers, which involves the existence of barriers that limit access conditions, whether geographical or financial. Although large commercial publishers predominantly dominate scientific production and subject it to the rules imposed by them, the Open Access movement whose first public declaration, the Budapest Declaration (BOAI), was in 2002, proposes significant changes that benefit the authors and the readers. This Movement has gained importance in Portugal since 2003, with the constitution of the first institutional repository at the national level. Institutional repositories have emerged as a tool for disseminating the scientific production of an institution to open the results of the research, both before publication and the preprint process and postprint, increase the visibility of work done by an investigator and his or her institution. The present study, which underwent an analysis of the copyright policies of INESC TEC most relevant scientific publications, allowed not only to realize that publishers are increasingly adopting policies that make it possible to self-archive publications in institutional repositories, all the work of raising awareness, not only for researchers but also for the institution and the whole society. The production of a set of recommendations, which go through the implementation of an institutional policy that encourages the self-archiving of the publications developed in the institutional scope in the repository, serves as a motto for a greater appreciation of the scientific production of INESC TEC