Foreground segmentation in depth imagery using depth and spatial dynamic models for video surveillance applications

Low-cost systems that can obtain a high-quality foreground segmentation almostindependently of the existing illumination conditions for indoor environments are verydesirable, especially for security and surveillance applications. In this paper, a novelforeground segmentation algorithm that uses only a Kinect depth sensor is proposedto satisfy the aforementioned system characteristics. This is achieved by combininga mixture of Gaussians-based background subtraction algorithm with a new Bayesiannetwork that robustly predicts the foreground/background regions between consecutivetime steps. The Bayesian network explicitly exploits the intrinsic characteristics ofthe depth data by means of two dynamic models that estimate the spatial and depthevolution of the foreground/background regions. The most remarkable contribution is thedepth-based dynamic model that predicts the changes in the foreground depth distributionbetween consecutive time steps. This is a key difference with regard to visible imagery,where the color/gray distribution of the foreground is typically assumed to be constant.Experiments carried out on two different depth-based databases demonstrate that theproposed combination of algorithms is able to obtain a more accurate segmentation of theforeground/background than other state-of-the art approaches.

Parallel Computational Intelligence-Based Multi-Camera Surveillance System

In this work, we present a multi-camera surveillance system based on the use of self-organizing neural networks to represent events on video. The system processes several tasks in parallel using GPUs (graphic processor units). It addresses multiple vision tasks at various levels, such as segmentation, representation or characterization, analysis and monitoring of the movement. These features allow the construction of a robust representation of the environment and interpret the behavior of mobile agents in the scene. It is also necessary to integrate the vision module into a global system that operates in a complex environment by receiving images from multiple acquisition devices at video frequency. Offering relevant information to higher level systems, monitoring and making decisions in real time, it must accomplish a set of requirements, such as: time constraints, high availability, robustness, high processing speed and re-configurability. We have built a system able to represent and analyze the motion in video acquired by a multi-camera network and to process multi-source data in parallel on a multi-GPU architecture.

Comparative Analysis of the Visual Performance After Cataract Surgery With Implantation of a Bifocal or Trifocal Diffractive IOL

PURPOSE: To evaluate and compare the visual, refractive, contrast sensitivity, and aberrometric outcomes with a diffractive bifocal and trifocal intraocular lens (IOL) of the same material and haptic design. METHODS: Sixty eyes of 30 patients undergoing bilateral cataract surgery were enrolled and randomly assigned to one of two groups: the bifocal group, including 30 eyes implanted with the bifocal diffractive IOL AT LISA 801 (Carl Zeiss Meditec, Jena, Germany), and the trifocal group, including eyes implanted with the trifocal diffractive IOL AT LISA tri 839 MP (Carl Zeiss Meditec). Analysis of visual and refractive outcomes, contrast sensitivity, ocular aberrations (OPD-Scan III; Nidek, Inc., Gagamori, Japan), and defocus curve were performed during a 3-month follow-up period. RESULTS: No statistically significant differences between groups were found in 3-month postoperative uncorrected and corrected distance visual acuity (P > .21). However, uncorrected, corrected, and distance-corrected near and intermediate visual acuities were significantly better in the trifocal group (P < .01). No significant differences between groups were found in postoperative spherical equivalent (P = .22). In the binocular defocus curve, the visual acuity was significantly better for defocus of -0.50 to -1.50 diopters in the trifocal group (P < .04) and -3.50 to -4.00 diopters in the bifocal group (P < .03). No statistically significant differences were found between groups in most of the postoperative corneal, internal, and ocular aberrations (P > .31), and in contrast sensitivity for most frequencies analyzed (P > .15). CONCLUSIONS: Trifocal diffractive IOLs provide significantly better intermediate vision over bifocal IOLs, with equivalent postoperative levels of visual and ocular optical quality.

Human Behaviour Recognition based on Trajectory Analysis using Neural Networks

Automated human behaviour analysis has been, and still remains, a challenging problem. It has been dealt from different points of views: from primitive actions to human interaction recognition. This paper is focused on trajectory analysis which allows a simple high level understanding of complex human behaviour. It is proposed a novel representation method of trajectory data, called Activity Description Vector (ADV) based on the number of occurrences of a person is in a specific point of the scenario and the local movements that perform in it. The ADV is calculated for each cell of the scenario in which it is spatially sampled obtaining a cue for different clustering methods. The ADV representation has been tested as the input of several classic classifiers and compared to other approaches using CAVIAR dataset sequences obtaining great accuracy in the recognition of the behaviour of people in a Shopping Centre.

The orchestration of modes and EFL audio-visual comprehension: A multimodal discourse analysis of vodcasts

This thesis explores the role of multimodality in language learners’ comprehension, and more specifically, the effects on students’ audio-visual comprehension when different orchestrations of modes appear in the visualization of vodcasts. Firstly, I describe the state of the art of its three main areas of concern, namely the evolution of meaning-making, Information and Communication Technology (ICT), and audio-visual comprehension. One of the most important contributions in the theoretical overview is the suggested integrative model of audio-visual comprehension, which attempts to explain how students process information received from different inputs. Secondly, I present a study based on the following research questions: ‘Which modes are orchestrated throughout the vodcasts?’, ‘Are there any multimodal ensembles that are more beneficial for students’ audio-visual comprehension?’, and ‘What are the students’ attitudes towards audio-visual (e.g., vodcasts) compared to traditional audio (e.g., audio tracks) comprehension activities?’. Along with these research questions, I have formulated two hypotheses: Audio-visual comprehension improves when there is a greater number of orchestrated modes, and students have a more positive attitude towards vodcasts than traditional audios when carrying out comprehension activities. The study includes a multimodal discourse analysis, audio-visual comprehension tests, and students’ questionnaires. The multimodal discourse analysis of two British Council’s language learning vodcasts, entitled English is GREAT and Camden Fashion, using ELAN as the multimodal annotation tool, shows that there are a variety of multimodal ensembles of two, three and four modes. The audio-visual comprehension tests were given to 40 Spanish students, learning English as a foreign language, after the visualization of vodcasts. These comprehension tests contain questions related to specific orchestrations of modes appearing in the vodcasts. The statistical analysis of the test results, using repeated-measures ANOVA, reveal that students obtain better audio-visual comprehension results when the multimodal ensembles are constituted by a greater number of orchestrated modes. Finally, the data compiled from the questionnaires, conclude that students have a more positive attitude towards vodcasts in comparison to traditional audio listenings. Results from the audio-visual comprehension tests and questionnaires prove the two hypotheses of this study.

Phylogenetic position and ultrastructure of two Dermocystidium species (Ichthyosporea) from the common perch (Perca fluviatilis)

Sequences of small-subunit rRNA genes were determined for Dermocystidium percae and a new Dermocystidium species established as D. fennicum sp. n. from perch in Finland. On the basis of alignment and phylogenetic analysis both species were placed in the Dermocystidium-Rhinosporidium clade within Ichthyosporea, D. fennicum as a specific sister taxon to D. salmonis, and D. percae in a clade different from D. fennicum. The ultrastructures of both species well agree with the characteristics approved within Ichthyosporea: walled spores produce uniflagellate zoospores lacking a collar or cortical alveoli. The two Dermocystidium species resemble Rhinosporidium seeberi (as described by light microscope), a member of the nearest relative genus, but differ in that in R. seeberi plasmodia have thousands of nuclei discernible, endospores are discharged through a pore in the wall of the sporangium, and zoospores have not been revealed. The plasmodial stages of both Dermocystidium species have a most unusual behaviour of nuclei, although we do not actually know how the nuclei transform during the development. Early stages have an ordinary nucleus with double, fenestrated envelope. In middle-aged plasmodia ordinary nuclei seem to be totally absent or are only seldom discernible until prior to sporogony, when rather numerous nuclei again reappear. Meanwhile single-membrane vacuoles with coarsely granular content, or complicated membranous systems were discernible. Ordinary nuclei may be re-formed within these vacuoles or systems. In D. percae small canaliculi and in D. fennicum minute vesicles may aid the nucleus-cytoplasm interchange of matter before formation of double-membrane-enveloped nuclei. Dermocystidium represents a unique case when a stage of the life cycle of an eukaryote lacks a typical nucleus.

Contextual anomaly detection in crowded surveillance scenes

This work addresses the problem of detecting human behavioural anomalies in crowded surveillance environments. We focus in particular on the problem of detecting subtle anomalies in a behaviourally heterogeneous surveillance scene. To reach this goal we implement a novel unsupervised context-aware process. We propose and evaluate a method of utilising social context and scene context to improve behaviour analysis. We find that in a crowded scene the application of Mutual Information based social context permits the ability to prevent self-justifying groups and propagate anomalies in a social network, granting a greater anomaly detection capability. Scene context uniformly improves the detection of anomalies in both datasets. The strength of our contextual features is demonstrated by the detection of subtly abnormal behaviours, which otherwise remain indistinguishable from normal behaviour.

Early warning systems for cyber defence

Cybercriminals ramp up their efforts with sophisticated techniques while defenders gradually update their typical security measures. Attackers often have a long-term interest in their targets. Due to a number of factors such as scale, architecture and nonproductive traffic however it makes difficult to detect them using typical intrusion detection techniques. Cyber early warning systems (CEWS) aim at alerting such attempts in their nascent stages using preliminary indicators. Design and implementation of such systems involves numerous research challenges such as generic set of indicators, intelligence gathering, uncertainty reasoning and information fusion. This paper discusses such challenges and presents the reader with compelling motivation. A carefully deployed empirical analysis using a real world attack scenario and a real network traffic capture is also presented.

Bayesian alignment of continuous molecular shapes using random fields

Statistical methodology is proposed for comparing molecular shapes. In order to account for the continuous nature of molecules, classical shape analysis methods are combined with techniques used for predicting random fields in spatial statistics. Applying a modification of Procrustes analysis, Bayesian inference is carried out using Markov chain Monte Carlo methods for the pairwise alignment of the resulting molecular fields. Superimposing entire fields rather than the configuration matrices of nuclear positions thereby solves the problem that there is usually no clear one--to--one correspondence between the atoms of the two molecules under consideration. Using a similar concept, we also propose an adaptation of the generalised Procrustes analysis algorithm for the simultaneous alignment of multiple molecular fields. The methodology is applied to a dataset of 31 steroid molecules.

New perspectives in statistical mechanics and high-dimensional inference

The main purpose of this thesis is to go beyond two usual assumptions that accompany theoretical analysis in spin-glasses and inference: the i.i.d. (independently and identically distributed) hypothesis on the noise elements and the finite rank regime. The first one appears since the early birth of spin-glasses. The second one instead concerns the inference viewpoint. Disordered systems and Bayesian inference have a well-established relation, evidenced by their continuous cross-fertilization. The thesis makes use of techniques coming both from the rigorous mathematical machinery of spin-glasses, such as the interpolation scheme, and from Statistical Physics, such as the replica method. The first chapter contains an introduction to the Sherrington-Kirkpatrick and spiked Wigner models. The first is a mean field spin-glass where the couplings are i.i.d. Gaussian random variables. The second instead amounts to establish the information theoretical limits in the reconstruction of a fixed low rank matrix, the “spike”, blurred by additive Gaussian noise. In chapters 2 and 3 the i.i.d. hypothesis on the noise is broken by assuming a noise with inhomogeneous variance profile. In spin-glasses this leads to multi-species models. The inferential counterpart is called spatial coupling. All the previous models are usually studied in the Bayes-optimal setting, where everything is known about the generating process of the data. In chapter 4 instead we study the spiked Wigner model where the prior on the signal to reconstruct is ignored. In chapter 5 we analyze the statistical limits of a spiked Wigner model where the noise is no longer Gaussian, but drawn from a random matrix ensemble, which makes its elements dependent. The thesis ends with chapter 6, where the challenging problem of high-rank probabilistic matrix factorization is tackled. Here we introduce a new procedure called "decimation" and we show that it is theoretically to perform matrix factorization through it.

Gravitational waves as dark sirens: an astrophysical and cosmological analysis

Despite the success of the ΛCDM model in describing the Universe, a possible tension between early- and late-Universe cosmological measurements is calling for new independent cosmological probes. Amongst the most promising ones, gravitational waves (GWs) can provide a self-calibrated measurement of the luminosity distance. However, to obtain cosmological constraints, additional information is needed to break the degeneracy between parameters in the gravitational waveform. In this thesis, we exploit the latest LIGO-Virgo-KAGRA Gravitational Wave Transient Catalog (GWTC-3) of GW sources to constrain the background cosmological parameters together with the astrophysical properties of Binary Black Holes (BBHs), using information from their mass distribution. We expand the public code MGCosmoPop, previously used for the application of this technique, by implementing a state-of-the-art model for the mass distribution, needed to account for the presence of non-trivial features, i.e. a truncated power law with two additional Gaussian peaks, referred to as Multipeak. We then analyse GWTC-3 comparing this model with simpler and more commonly adopted ones, both in the case of fixed and varying cosmology, and assess their goodness-of-fit with different model selection criteria, and their constraining power on the cosmological and population parameters. We also start to explore different sampling methods, namely Markov Chain Monte Carlo and Nested Sampling, comparing their performances and evaluating the advantages of both. We find concurring evidence that the Multipeak model is favoured by the data, in line with previous results, and show that this conclusion is robust to the variation of the cosmological parameters. We find a constraint on the Hubble constant of H0 = 61.10+38.65−22.43 km/s/Mpc (68% C.L.), which shows the potential of this method in providing independent constraints on cosmological parameters. The results obtained in this work have been included in [1].

Análise bayesiana do modelo de herança monogênica no melhoramento vegetal: um exemplo com abobrinha

A common breeding strategy is to carry out basic studies to investigate the hypothesis of a single gene controlling the trait (major gene) with or without polygenes of minor effect. In this study we used Bayesian inference to fit genetic additive-dominance models of inheritance to plant breeding experiments with multiple generations. Normal densities with different means, according to the major gene genotype, were considered in a linear model in which the design matrix of the genetic effects had unknown coefficients (which were estimated in individual basis). An actual data set from an inheritance study of partenocarpy in zucchini (Cucurbita pepo L.) was used for illustration. Model fitting included posterior probabilities for all individual genotypes. Analysis agrees with results in the literature but this approach was far more efficient than previous alternatives assuming that design matrix was known for the generations. Partenocarpy in zucchini is controlled by a major gene with important additive effect and partial dominance.

Assessing influence in survival data with a cure fraction and covariates

Diagnostic methods have been an important tool in regression analysis to detect anomalies, such as departures from error assumptions and the presence of outliers and influential observations with the fitted models. Assuming censored data, we considered a classical analysis and Bayesian analysis assuming no informative priors for the parameters of the model with a cure fraction. A Bayesian approach was considered by using Markov Chain Monte Carlo Methods with Metropolis-Hasting algorithms steps to obtain the posterior summaries of interest. Some influence methods, such as the local influence, total local influence of an individual, local influence on predictions and generalized leverage were derived, analyzed and discussed in survival data with a cure fraction and covariates. The relevance of the approach was illustrated with a real data set, where it is shown that, by removing the most influential observations, the decision about which model best fits the data is changed.

Phylogenetic position of the acariform mites: sensitivity to homology assessment under total evidence

Background: Mites (Acari) have traditionally been treated as monophyletic, albeit composed of two major lineages: Acariformes and Parasitiformes. Yet recent studies based on morphology, molecular data, or combinations thereof, have increasingly drawn their monophyly into question. Furthermore, the usually basal (molecular) position of one or both mite lineages among the chelicerates is in conflict to their morphology, and to the widely accepted view that mites are close relatives of Ricinulei. Results: The phylogenetic position of the acariform mites is examined through employing SSU, partial LSU sequences, and morphology from 91 chelicerate extant terminals (forty Acariformes). In a static homology framework, molecular sequences were aligned using their secondary structure as guide, whereby regions of ambiguous alignment were discarded, and pre-aligned sequences analyzed under parsimony and different mixed models in a Bayesian inference. Parsimony and Bayesian analyses led to trees largely congruent concerning infraordinal, well-supported branches, but with low support for inter-ordinal relationships. An exception is Solifugae + Acariformes (P. P = 100%, J. = 0.91). In a dynamic homology framework, two analyses were run: a standard POY analysis and an analysis constrained by secondary structure. Both analyses led to largely congruent trees; supporting a (Palpigradi (Solifugae Acariformes)) clade and Ricinulei as sister group of Tetrapulmonata with the topology (Ricinulei (Amblypygi (Uropygi Araneae))). Combined analysis with two different morphological data matrices were run in order to evaluate the impact of constraining the analysis on the recovered topology when employing secondary structure as a guide for homology establishment. The constrained combined analysis yielded two topologies similar to the exclusively molecular analysis for both morphological matrices, except for the recovery of Pedipalpi instead of the (Uropygi Araneae) clade. The standard (direct optimization) POY analysis, however, led to the recovery of trees differing in the absence of the otherwise well-supported group Solifugae + Acariformes. Conclusions: Previous studies combining ribosomal sequences and morphology often recovered topologies similar to purely morphological analyses of Chelicerata. The apparent stability of certain clades not recovered here, like Haplocnemata and Acari, is regarded as a byproduct of the way the molecular homology was previously established using the instrumentalist approach implemented in POY. Constraining the analysis by a priori homology assessment is defended here as a way of maintaining the severity of the test when adding new data to the analysis. Although the strength of the method advocated here is keeping phylogenetic information from regions usually discarded in an exclusively static homology framework; it still has the inconvenience of being uninformative on the effect of alignment ambiguity on resampling methods of clade support estimation. Finally, putative morphological apomorphies of Solifugae + Acariformes are the reduction of the proximal cheliceral podomere, medial abutting of the leg coxae, loss of sperm nuclear membrane, and presence of differentiated germinative and secretory regions in the testis delivering their products into a common lumen.

Prey capture and accommodation in the sandlance, Limnichthyes fasciatus (Creediidae; Teleostei)

The eyes of the sandlance, Limnichthyes fasciatus (Creediidae. Teleostei) move independently and possess a refractive cornea, a convexiclivate fovea and a non-spherical lens giving rise to a wide separation of the nodal point from the axis of rotation of the eye much like that of a chameleon. To investigate this apparent convergence of the visual optics in these phylogenetically disparate species, we examine feeding behaviour and accommodation in the sandlance with special reference to the possibility that sandlances use accommodation as a depth cue to judge strike length. Frame-by-frame analysis of over 2000 strikes show a 100% success rate. Explosive strikes are completed in 50 ms over prey distances of four body lengths. Close-up video confirms that successful strikes can be initiated monocularly (both normally and after monocular occlusion) showing that binocular cues are not necessary to judge the length of a strike. Additional means of judging prey distance may also be derived from parallax information generated by rotation of the eye as suggested for chameleons. Using photorefraction on anaesthetised sandlances, accommodative changes were induced with acetylcholine and found to range between 120 D and 180 D at a speed of 600-720 D s(-1). The large range of accommodation (25% of the total power) is also thought to be mediated by corneal accommodation where the contraction of a unique cornealis muscle acts to change the corneal curvatures.