Multi-Camera very wide baseline feature matching based on view-adaptive junction detection

This paper presents a strategy for solving the feature matching problem in calibrated very wide-baseline camera settings. In this kind of settings, perspective distortion, depth discontinuities and occlusion represent enormous challenges. The proposed strategy addresses them by using geometrical information, specifically by exploiting epipolar-constraints. As a result it provides a sparse number of reliable feature points for which 3D position is accurately recovered. Special features known as junctions are used for robust matching. In particular, a strategy for refinement of junction end-point matching is proposed which enhances usual junction-based approaches. This allows to compute cross-correlation between perfectly aligned plane patches in both images, thus yielding better matching results. Evaluation of experimental results proves the effectiveness of the proposed algorithm in very wide-baseline environments.

Reality bites: Documentary photography and architectural realism = Fragmentos de realidad: Fotografía documental y realismo en arquitectura

En el día de hoy nos enfrentamos a una serie de desafíos económicos, geopolíticos y ambientales que apuntan hacia una transformación profunda del mundo tal y como lo conocemos. La arquitectura esta – siempre lo ha estado – imbricada en todos estos problemas. En nuestra actual condición de recursos limitados e injusticia global surge la necesidad de superar la dicotomía entre progreso y tradición, entre innovación y preservación – la urgencia de redefinir incluso cada uno de estos términos. Los tipos de crisis que encaramos ahora no se resolverán con mas tecnología y más crecimiento – se necesita también una profunda reevaluación de nuestros sistemas de valores e incluso de nuestra sensibilidad. En este contexto, la humilde contribución de esta tesis consiste en proponer la idea de un realismo en arquitectura, entendido como una actitud progresista y atenta a lo que ya existe, dispuesta a abrir los ojos al presente, a las condiciones y los problemas reales que nos rodean. Pensando en esta idea, resulta evidente que si bien el realismo carece de una definición clara en el campo de la arquitectura hoy, cuenta sin embargo con numerosos precedentes parciales, entre ellos algunos de los más notorios episodios de la historia de la arquitectura reciente. Al intentar confeccionar una lista provisional de arquitectos realistas en el último siglo, otro hecho se nos presenta: muchos, por no decir todos estos arquitectos, comparten una fijación por la fotografía, bien apropiándose del trabajo de fotógrafos contemporáneos, bien tomando sus propias imágenes como una forma de mirar fuera de sus estudios e incorporar la realidad del medio construido a sus proyectos. Parece entonces lógico pensar que la arquitectura, como disciplina visual, ha acudido a otra disciplina visual en búsqueda de su propia respuesta al problema del realismo – dentro de este campo la fotografía reverbera con la arquitectura especialmente, ya que ambas son consideradas simultáneamente como practicas utilitarias y como parte de las bellas artes. Parece entonces lógico el organizar la investigación como una serie de casos, con la esperanza de que la acumulación de diversas instancias en las que la arquitectura ha acudido a la fotografía en su búsqueda de un realismo arrojara luz sobre las ideas más generales a debate. Por tanto, cada uno de los episodios en este texto se examina en sus propios términos, si bien una serie de interconexiones emergen a medida que el estudio procede con un suave orden cronológico. Hacia el final del texto cuestiones más grandes recobran protagonismo, a medida que las repercusiones políticas de nuestro estudio se hacen más patentes y comenzamos a interrogar las implicaciones contemporáneas y el potencial futuro de nuestra discusión sobre el realismo. ABSTRACT Today we are faced with a series of economic, geopolitical and environmental challenges that outline a deep transformation of the world as we know it. Architecture is – it has always been – ingrained in all of these problems. In our current condition of limited resources and global inequalities there is a necessity to overcome the dichotomy between progress and tradition, between innovation and preservation – an urgency to even redefine these terms altogether. The types of crises that we are facing will not be solved with more technology and more growth – a deep reevaluation of our systems of values and our sensibilities are also needed. In this context, the humble contribution of this text is to put forward the idea of an architectural realism, understood as an attitude that is both progressive and attentive to what is already in place, willing to open its eyes to the present and accept the real conditions and problems around us. In thinking about this prospect, it immediately becomes apparent that even if realism lacks a clear definition in the field of architecture today, there are numerous partial precedents for it, among them some of the most notorious episodes in the recent history of architecture. In crafting a tentative list of realist architects in the last century, another realization takes place: many, not to say all of these architects, have had a fixation with photography, either appropriating the work of contemporary photographers or taking photographs themselves as a way to look out their windows and bring the reality of the built environment into their practices. It seems then logical to think that architecture, as a visual discipline, has looked to other visual disciplines in search for its own take on the problem of realism – within this field, photography specially resonates with architecture, since both are regarded simultaneously as utilitarian practices and belonging to the fine arts. The idea then becomes to organize the research as a series of cases, with the hope that the accumulation of diverse instances in which architecture has approached photography in its realist drive will shed some light on the larger ideas at stake. Therefore, each of the episodes in this text is examined on its own terms, with a series of interconnections slowly emerging as our survey proceeds with a soft chronologic order. Towards the end of the study, larger issues regain relevance as the political repercussions of our inquiry become more pressing and we start to question the contemporary implications and future potentials of our discussion on realism.

Signal analysis and feature generation for pattern identification of partial discharges in high-voltage equipment

This paper proposes a method for the identification of different partial discharges (PDs) sources through the analysis of a collection of PD signals acquired with a PD measurement system. This method, robust and sensitive enough to cope with noisy data and external interferences, combines the characterization of each signal from the collection, with a clustering procedure, the CLARA algorithm. Several features are proposed for the characterization of the signals, being the wavelet variances, the frequency estimated with the Prony method, and the energy, the most relevant for the performance of the clustering procedure. The result of the unsupervised classification is a set of clusters each containing those signals which are more similar to each other than to those in other clusters. The analysis of the classification results permits both the identification of different PD sources and the discrimination between original PD signals, reflections, noise and external interferences. The methods and graphical tools detailed in this paper have been coded and published as a contributed package of the R environment under a GNU/GPL license.

Speech Signals Feature Extraction Model for a Speaker’s Gender and Age Identification System

Durante el proceso de producción de voz, los factores anatómicos, fisiológicos o psicosociales del individuo modifican los órganos resonadores, imprimiendo en la voz características particulares. Los sistemas ASR tratan de encontrar los matices característicos de una voz y asociarlos a un individuo o grupo. La edad y sexo de un hablante son factores intrínsecos que están presentes en la voz. Este trabajo intenta diferenciar esas características, aislarlas y usarlas para detectar el género y la edad de un hablante. Para dicho fin, se ha realizado el estudio y análisis de las características basadas en el pulso glótico y el tracto vocal, evitando usar técnicas clásicas (como pitch y sus derivados) debido a las restricciones propias de dichas técnicas. Los resultados finales de nuestro estudio alcanzan casi un 100% en reconocimiento de género mientras en la tarea de reconocimiento de edad el reconocimiento se encuentra alrededor del 80%. Parece ser que la voz queda afectada por el género del hablante y las hormonas, aunque no se aprecie en la audición. ABSTRACT Particular elements of the voice are printed during the speech production process and are related to anatomical and physiological factors of the phonatory system or psychosocial factors acquired by the speaker. ASR systems attempt to find those peculiar nuances of a voice and associate them to an individual or a group. Age and gender are inherent factors to the speaker which may be represented in voice. This work attempts to differentiate those characteristics, isolate them and use them to detect speaker’s gender and age. Features based on glottal pulse and vocal tract are studied and analyzed in order to achieve good results in both tasks. Classical methodologies (such as pitch and derivates) are avoided since the requirements of those techniques may be too restrictive. The final scores achieve almost 100% in gender recognition whereas in age recognition those scores are around 80%. Factors related to the gender and hormones seem to affect the voice although they are not audible.

A survey of feature selection in Internet traffic characterization

In the last decade, the research community has focused on new classification methods that rely on statistical characteristics of Internet traffic, instead of pre-viously popular port-number-based or payload-based methods, which are under even bigger constrictions. Some research works based on statistical characteristics generated large fea-ture sets of Internet traffic; however, nowadays it?s impossible to handle hun-dreds of features in big data scenarios, only leading to unacceptable processing time and misleading classification results due to redundant and correlative data. As a consequence, a feature selection procedure is essential in the process of Internet traffic characterization. In this paper a survey of feature selection methods is presented: feature selection frameworks are introduced, and differ-ent categories of methods are briefly explained and compared; several proposals on feature selection in Internet traffic characterization are shown; finally, future application of feature selection to a concrete project is proposed.

Enhancing regression models for complex systems using evolutionary techniques for feature engineering

This work proposes an automatic methodology for modeling complex systems. Our methodology is based on the combination of Grammatical Evolution and classical regression to obtain an optimal set of features that take part of a linear and convex model. This technique provides both Feature Engineering and Symbolic Regression in order to infer accurate models with no effort or designer's expertise requirements. As advanced Cloud services are becoming mainstream, the contribution of data centers in the overall power consumption of modern cities is growing dramatically. These facilities consume from 10 to 100 times more power per square foot than typical office buildings. Modeling the power consumption for these infrastructures is crucial to anticipate the effects of aggressive optimization policies, but accurate and fast power modeling is a complex challenge for high-end servers not yet satisfied by analytical approaches. For this case study, our methodology minimizes error in power prediction. This work has been tested using real Cloud applications resulting on an average error in power estimation of 3.98%. Our work improves the possibilities of deriving Cloud energy efficient policies in Cloud data centers being applicable to other computing environments with similar characteristics.

Finite element code-based modeling of a multi-feature isolation system and passive alleviation of possible inner pounding

The existing seismic isolation systems are based on well-known and accepted physical principles, but they are still having some functional drawbacks. As an attempt of improvement, the Roll-N-Cage (RNC) isolator has been recently proposed. It is designed to achieve a balance in controlling isolator displacement demands and structural accelerations. It provides in a single unit all the necessary functions of vertical rigid support, horizontal flexibility with enhanced stability, resistance to low service loads and minor vibration, and hysteretic energy dissipation characteristics. It is characterized by two unique features that are a self-braking (buffer) and a self-recentering mechanism. This paper presents an advanced representation of the main and unique features of the RNC isolator using an available finite element code called SAP2000. The validity of the obtained SAP2000 model is then checked using experimental, numerical and analytical results. Then, the paper investigates the merits and demerits of activating the built-in buffer mechanism on both structural pounding mitigation and isolation efficiency. The paper addresses the problem of passive alleviation of possible inner pounding within the RNC isolator, which may arise due to the activation of its self-braking mechanism under sever excitations such as near-fault earthquakes. The results show that the obtained finite element code-based model can closely match and accurately predict the overall behavior of the RNC isolator with effectively small errors. Moreover, the inherent buffer mechanism of the RNC isolator could mitigate or even eliminate direct structure-tostructure pounding under severe excitation considering limited septation gaps between adjacent structures. In addition, the increase of inherent hysteretic damping of the RNC isolator can efficiently limit its peak displacement together with the severity of the possibly developed inner pounding and, therefore, alleviate or even eliminate the possibly arising negative effects of the buffer mechanism on the overall RNC-isolated structural responses.

A study of feature combination for vehicle detection based on image processing

Video analytics play a critical role in most recent traffic monitoring and driver assistance systems. In this context, the correct detection and classification of surrounding vehicles through image analysis has been the focus of extensive research in the last years. Most of the pieces of work reported for image-based vehicle verification make use of supervised classification approaches and resort to techniques, such as histograms of oriented gradients (HOG), principal component analysis (PCA), and Gabor filters, among others. Unfortunately, existing approaches are lacking in two respects: first, comparison between methods using a common body of work has not been addressed; second, no study of the combination potentiality of popular features for vehicle classification has been reported. In this study the performance of the different techniques is first reviewed and compared using a common public database. Then, the combination capabilities of these techniques are explored and a methodology is presented for the fusion of classifiers built upon them, taking into account also the vehicle pose. The study unveils the limitations of single-feature based classification and makes clear that fusion of classifiers is highly beneficial for vehicle verification.

Multiple feature points representation in target localization of wireless visual sensor networks

This paper discusses the target localization problem in wireless visual sensor networks. Additive noises and measurement errors will affect the accuracy of target localization when the visual nodes are equipped with low-resolution cameras. In the goal of improving the accuracy of target localization without prior knowledge of the target, each node extracts multiple feature points from images to represent the target at the sensor node level. A statistical method is presented to match the most correlated feature point pair for merging the position information of different sensor nodes at the base station. Besides, in the case that more than one target exists in the field of interest, a scheme for locating multiple targets is provided. Simulation results show that, our proposed method has desirable performance in improving the accuracy of locating single target or multiple targets. Results also show that the proposed method has a better trade-off between camera node usage and localization accuracy.

Feature issue introduction: light, energy and the environment, 2014

This feature issue highlights contributions from authors who presented their research at the OSA Light, Energy and the Environment Congress, held in Canberra, Australia from 2-5 December, 2014.

Feature integration in pattern perception

The human visual system is able to effortlessly integrate local features to form our rich perception of patterns, despite the fact that visual information is discretely sampled by the retina and cortex. By using a novel perturbation technique, we show that the mechanisms by which features are integrated into coherent percepts are scale-invariant and nonlinear (phase and contrast polarity independent). They appear to operate by assigning position labels or “place tags” to each feature. Specifically, in the first series of experiments, we show that the positional tolerance of these place tags in foveal, and peripheral vision is about half the separation of the features, suggesting that the neural mechanisms that bind features into forms are quite robust to topographical jitter. In the second series of experiment, we asked how many stimulus samples are required for pattern identification by human and ideal observers. In human foveal vision, only about half the features are needed for reliable pattern interpolation. In this regard, human vision is quite efficient (ratio of ideal to real ≈ 0.75). Peripheral vision, on the other hand is rather inefficient, requiring more features, suggesting that the stimulus may be relatively underrepresented at the stage of feature integration.

The central structural feature of the membrane fusion protein subunit from the Ebola virus glycoprotein is a long triple-stranded coiled coil

The ectodomain of the Ebola virus Gp2 glycoprotein was solubilized with a trimeric, isoleucine zipper derived from GCN4 (pIIGCN4) in place of the hydrophobic fusion peptide at the N terminus. This chimeric molecule forms a trimeric, highly α-helical, and very thermostable molecule, as determined by chemical crosslinking and circular dichroism. Electron microscopy indicates that Gp2 folds into a rod-like structure like influenza HA2 and HIV-1 gp41, providing further evidence that viral fusion proteins from diverse families such as Orthomyxoviridae (Influenza), Retroviridae (HIV-1), and Filoviridae (Ebola) share common structural features, and suggesting a common membrane fusion mechanism.

Formation of temporal-feature maps by axonal propagation of synaptic learning

Computational maps are of central importance to a neuronal representation of the outside world. In a map, neighboring neurons respond to similar sensory features. A well studied example is the computational map of interaural time differences (ITDs), which is essential to sound localization in a variety of species and allows resolution of ITDs of the order of 10 μs. Nevertheless, it is unclear how such an orderly representation of temporal features arises. We address this problem by modeling the ontogenetic development of an ITD map in the laminar nucleus of the barn owl. We show how the owl's ITD map can emerge from a combined action of homosynaptic spike-based Hebbian learning and its propagation along the presynaptic axon. In spike-based Hebbian learning, synaptic strengths are modified according to the timing of pre- and postsynaptic action potentials. In unspecific axonal learning, a synapse's modification gives rise to a factor that propagates along the presynaptic axon and affects the properties of synapses at neighboring neurons. Our results indicate that both Hebbian learning and its presynaptic propagation are necessary for map formation in the laminar nucleus, but the latter can be orders of magnitude weaker than the former. We argue that the algorithm is important for the formation of computational maps, when, in particular, time plays a key role.

Seeing properties of an invisible object: Feature inheritance and shine-through

We characterize a class of spatio-temporal illusions with two complementary properties. Firstly, if a vernier stimulus is flashed for a short time on a monitor and is followed immediately by a grating, the latter can express features of the vernier, such as its offset, its orientation, or its motion (feature inheritance). Yet the vernier stimulus itself remains perceptually invisible. Secondly, the vernier can be rendered visible by presenting gratings with a larger number of elements (shine-through). Under these conditions, subjects perceive two independent “objects” each carrying their own features. Transition between these two domains can be effected by subtle changes in the spatio-temporal layout of the grating. This should allow psychophysicists and electrophysiologists to investigate feature binding in a precise and quantitative manner.

A novel information theory method for filter feature selection

In this paper, we propose a novel filter for feature selection. Such filter relies on the estimation of the mutual information between features and classes. We bypass the estimation of the probability density function with the aid of the entropic-graphs approximation of Rényi entropy, and the subsequent approximation of the Shannon one. The complexity of such bypassing process does not depend on the number of dimensions but on the number of patterns/samples, and thus the curse of dimensionality is circumvented. We show that it is then possible to outperform a greedy algorithm based on the maximal relevance and minimal redundancy criterion. We successfully test our method both in the contexts of image classification and microarray data classification.