More is Better: 3D Human Pose Estimation from Complementary Data Sources

Computer Vision (CV) research has been playing a strategic role in many different complex scenarios that are becoming fundamental components in our everyday life. From Augmented/Virtual reality (AR/VR) to Human-Robot interactions, having a visual interpretation of the surrounding world is the first and most important step to develop new advanced systems. As in other research areas, the boost in performance in Computer Vision algorithms has to be mainly attributed to the widespread usage of deep neural networks. Rather than selecting handcrafted features, such approaches identify which are the best features needed to solve a specific task, by learning them from a corpus of carefully annotated data. Such important property of these neural networks comes with a price: they need very large data collections to learn from. Collecting data is a time consuming and expensive operation that varies, being much harder for some tasks than others. In order to limit additional data collection, we therefore need to carefully design models that can extract as much information as possible from already available dataset, even those collected for neighboring domains. In this work I focus on exploring different solutions for and important research problem in Computer Vision, 3D human pose estimation, that is the task of estimating the 3D skeletal representation of a person characterized in an image/s. This has been done for several configurations: monocular camera, multi-view systems and from egocentric perspectives. First, from a single external front facing camera a semi-supervised approach is used to regress the set of 3D joint positions of the represented person. This is done by fully exploiting all of the available information at all the levels of the network, in a novel manner, as well as allowing the model to be trained with partially labelled data. A multi-camera 3D human pose estimation system is introduced by designing a network trainable in a semi-supervised or even unsupervised manner in a multiview system. Unlike standard motion-captures algorithm, demanding a long and time consuming configuration setup at the beginning of each capturing session, this novel approach requires little to none initial system configuration. Finally, a novel architecture is developed to work in a very specific and significantly harder configuration: 3D human pose estimation when using cameras embedded in a head mounted display (HMD). Due to the limited data availability, the model needs to carefully extract information from the data to properly generalize on unseen images. This is particularly useful in AR/VR use case scenarios, demonstrating the versatility of our network to various working conditions

Vitis OneGenE: a causality-based approach to generate gene networks in Vitis vinifera sheds light on the laccase and dirigent gene families

9openInternationalBothThe abundance of transcriptomic data and the development of causal inference methods have paved the way for gene network analyses in grapevine. Vitis OneGenE is a transcriptomic data mining tool that finds direct correlations between genes, thus producing association networks. As a proof of concept, the stilbene synthase gene regulatory network obtained with OneGenE has been compared with published co-expression analysis and experimental data, including cistrome data for MYB stilbenoid regulators. As a case study, the two secondary metabolism pathways of stilbenoids and lignin synthesis were explored. Several isoforms of laccase, peroxidase, and dirigent protein genes, putatively involved in the final oxidative oligomerization steps, were identified as specifically belonging to either one of these pathways. Manual curation of the predicted sequences exploiting the last available genome assembly, and the integration of phylogenetic and OneGenE analyses, identified a group of laccases exclusively present in grapevine and related to stilbenoids. Here we show how network analysis by OneGenE can accelerate knowledge discovery by suggesting new candidates for functional characterization and application in breeding programs.openPilati, Stefania; Malacarne, Giulia; Navarro-Payá, David; Tomè, Gabriele; Riscica, Laura; Cavecchia, Valter; Matus, José Tomás; Moser, Claudio; Blanzieri, EnricoPilati, S.; Malacarne, G.; Navarro-Payá, D.; Tomè, G.; Riscica, L.; Cavecchia, V.; Matus, J.T.; Moser, C.; Blanzieri, E

Real-time embedded intelligence system : emotion recognition on Raspberry Pi with Intel NCS

Convolutional Neural Networks (CNNs) have exhibited certain human-like performance on computer vision related tasks. Over the past few years since they have outperformed conventional algorithms in a range of image processing problems. However, to utilise a CNN model with millions of free parameters on a source limited embedded system is a challenging problem. The Intel Neural Compute Stick (NCS) provides a possible route for running largescale neural networks on a low cost, low power, portable unit. In this paper, we propose a CNN based Raspberry Pi system that can run a pre-trained inference model in real time with an average power consumption of 6.2W. The Intel Movidius NCS, which avoids requirements of expensive processing units e.g. GPU, FPGA. The system is demonstrated using a facial image-based emotion recogniser. A fine-tuned CNN model is designed and trained to perform inference on each captured frame within the processing modules of NCS

Investigation of oscillation frequency and disorder induced dynamic phase transitions in a quenched-bond diluted Ising ferromagnet

Frequency evolutions of hysteresis loop area and hysteresis tools such as remanence and coercivity of a kinetic Ising model in the presence of quenched bond dilution are investigated in detail. The kinetic equation describing the time dependence of the magnetization is derived by means of effective-field theory with single-site correlations. It is found that the frequency dispersions of hysteresis loop area, remanence and coercivity strongly depend on the quenched bond randomness, as well as applied field amplitude and oscillation frequency. In addition, the shape of the hysteresis curves for a wide variety of Hamiltonian parameters is studied and some interesting behaviors are found. Finally, a comparison of our observations with those of recently published studies is represented and it is shown that there exists a qualitatively good agreement.Comment: 11 pages, 8 figure

Hysteretic response characteristics and dynamic phase transition via site dilution in the kinetic Ising model

The decay of the hysteresis loop area of the system, which is obeying a site diluted kinetic Ising model, is considered by the disorder parameter using the effective field theory analysis. The exhibition focuses on the understanding of external field frequency, amplitude and the site concentration dependency of the hysteresis loop area for several powerful treatments. Important characteristics of the hysteretic response, such as frequency dispersion, effect of domain nucleation phenomenon on the dynamic process etc. has been introduced together with well known other characteristics. An attempt has been made to explain the relations between the competing time scales (intrinsic microscopic relaxation time of the system and the time period of the external oscillatory field) and the shape of the response. As a result of the detailed investigations, existence of essentially three, particularly four types of dispersion curves have been propounded.Comment: 16 pages, 8 figure

Stationary State Solutions of a Bond Diluted Kinetic Ising Model: An Effective-Field Theory Analysis

We have examined the stationary state solutions of a bond diluted kinetic Ising model under a time dependent oscillating magnetic field within the effective-field theory (EFT) for a honeycomb lattice $(q=3)$. Time evolution of the system has been modeled with a formalism of master equation. The effects of the bond dilution, as well as the frequency $(\omega)$ and amplitude $(h/J)$ of the external field on the dynamic phase diagrams have been discussed in detail. We have found that the system exhibits the first order phase transition with a dynamic tricritical point (DTCP) at low temperature and high amplitude regions, in contrast to the previously published results for the pure case \cite{Ling}. Bond dilution process on the kinetic Ising model gives rise to a number of interesting and unusual phenomena such as reentrant phenomena and has a tendency to destruct the first-order transitions and the DTCP. Moreover, we have investigated the variation of the bond percolation threshold as functions of the amplitude and frequency of the oscillating field.Comment: 8 pages, 4 figure

Results from the ULTRA experiment in the framework of the EUSO project

The detection of Cerenkov light from EAS in a delayed coincidence with fluorescence light gives a strong signature to discriminate protons and neutrinos in cosmic rays. For this purpose, the ULTRA experiment has been designed with 2 detectors: a small EAS array (ETscope) and an UV optical device including wide field (Belenos) and narrow field (UVscope) Cerenkov light detectors. The array measures the shower size and the arrival direction of the incoming EAS, while the UV devices, pointing both to zenith and nadir, are used to determine the amount of direct and diffused coincident Cerenkov light. This information, provided for different diffusing surfaces, will be used to verify the possibility of detecting from Space the Cerenkov light produced by UHECRs with the EUSO experiment, on board the ISS

Natural deep eutectic solvents present in plant exudates? A case study on the saps of Droseraspecies

Plant science

Comprehension of progressive taxation and attitude towards redistribution

openLa ricerca presentata si propone di indagare la relazione tra comprensione del sistema di tassazione e atteggiamento nei confronti del sistema stesso. Indaga inoltre la relazione tra punteggio al cognitive reflection test e supporto alla tassazione progressiva e la relazione tra emozioni negative suscitate dalle tasse e atteggiamento verso le stesse. Lo studio si struttura in due condizioni tra i partecipanti, in cui viene introdotto l'argomento delle tasse attraverso un video esplicativo o una tabella non spiegata. La ricerca si propone di trovare un modo efficace per parlare del sistema di tassazione e di tasse con i cittadini, favorendo in loro l'acquisizione di un atteggiamento più positivo nei confronti delle tasse e della tassazione progressiva in particolare. Attraverso l'impiego del modello del modello di probabilità di elaborazione di Petty e Cacioppo (1981) vogliamo capire se il video esplicativo funzioni meglio della tabella per aiutare le persone a comprendere il sistema di tassazione