Fast Fight Detection

Action recognition has become a hot topic within computer vision. However, the action recognition community has focused mainly on relatively simple actions like clapping, walking, jogging, etc. The detection of specific events with direct practical use such as fights or in general aggressive behavior has been comparatively less studied. Such capability may be extremely useful in some video surveillance scenarios like prisons, psychiatric centers or even embedded in camera phones. As a consequence, there is growing interest in developing violence detection algorithms. Recent work considered the well-known Bag-of-Words framework for the specific problem of fight detection. Under this framework, spatio-temporal features are extracted from the video sequences and used for classification. Despite encouraging results in which high accuracy rates were achieved, the computational cost of extracting such features is prohibitive for practical applications. This work proposes a novel method to detect violence sequences. Features extracted from motion blobs are used to discriminate fight and non-fight sequences. Although the method is outperformed in accuracy by state of the art, it has a significantly faster computation time thus making it amenable for real-time applications

Detecció de punts de referència en entorns urbans mitjançant visió per computador

Treballs Finals de Grau d'Enginyeria Informàtica, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2023, Director: Jordi Vitrià i Marca, Sergi Hernández i Alejandro López[en] This project aims to supply the ADD autonomous robot with a landmark detection system that should be able to easily integrate with the existing localization stack. Multiple landmark have been developed, but this project is centered on urban traffic signs. To be able to detect and classify the signs, three different methods are proposed: the first uses a convolutional neural network (CNN) to both detect and classify the signs; the second one uses a CNN to detect and another one to classify; the third, uses a CNN to detect and more traditional methods to classify. Multiple networks and optimizations are considered, with a strong emphasis with those on the YOLO family. These methods have been tested with the well known GTSDB and GTSRB, and some results have been comparable to the ones obtained in the state of the art. They are also tested in environments much more similar to the ones the robot will encounter, using a specially made dataset

Sobre la decidibilitat de problemes computacionals

Treballs Finals de Grau d'Enginyeria Informàtica, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2024, Director: Juan Carlos Martínez Alonso[en] The proposition in 1928 of David Hilbert’s Entscheidungsproblem, led to the development of the theory of computability, which seeks to understand what can and cannot be computed. This work aims to be an introduction to this field. During its development, the fundamental concepts of automata theory and formal languages will be shown, along with Turing machines and the Church-Turing thesis, to finally see that there are undecidable problems and show some examples of them

XMM-Newton and Deep Optical Observations of the OTELO fields: the Groth-Westphal Strip

OTELO (OSIRIS Tunable Emission Line Object Survey) will be carried out with the OSIRIS instrument at the 10 m GTC telescope at La Palma, and is aimed to be the deepest and richest survey of emission line objects to date. The deep narrow-band optical data from OSIRIS will be complemented by means of additional observations that include: (i) an exploratory broad-band survey that is already being carried out in the optical domain, (ii) FIR and sub-mm observations to be carried with the Herschel space telescope and the GTM, and (iii) deep X-Ray observations from XMM-Newton and Chandra.Here we present a preliminary analysis of public EPIC data of one of the OTELO targets,the Groth-Westphal strip, gathered from the XMM-Newton Science Archive (XSA). EPIC images are combined with optical BVRI data from our broadband survey carried out with the 4.2m WHT at La Palma. Distance-independent diagnostics (involving X/O ratio, hardness ratios, B/T ratio) are tested.Comment: 2 pages, 2 figures, uses graphicx package. To appear in proceedings of "The X-Ray Universe 2005", San Lorenzo del Escorial, Spain, September 26-30, 200

Progress in the study of genome size evolution in Asteraceae: analysis of the last update

The Genome Size in Asteraceae database (GSAD, http://www.asteraceaegenomesize.com) has been recently updated, with data from papers published or in press until July 2018. This constitutes the third release of GSAD, currently containing 4350 data entries for 1496 species, which represent a growth of 22.52% in the number of species with available genome size data compared with the previous release, and a growth of 57.72% in terms of entries. Approximately 6% of Asteraceae species are covered in terms of known genome sizes. The number of source papers included in this release (198) means a 48.87% increase with respect to release 2.0. The significant data increase was exploited to study the genome size evolution in the family from a phylogenetic perspective. Our results suggest that the role of chromosome number in genome size diversity within Asteraceae is basically associated to polyploidy, while dysploidy would only cause minor variation in the DNA amount along the family. Among diploid taxa, we found that the evolution of genome size shows a strong phylogenetic signal. However, this trait does not seem to evolve evenly across the phylogeny, but there could be significant scale and clade-dependent patterns. Our analyses indicate that the phylogenetic signal is stronger at low taxonomic levels, with certain tribes standing out as hotspots of autocorrelation between genome size and phylogeny. Finally, we also observe meaningful associations among nuclear DNA content on Asteraceae species and other phenotypical and ecological traits (i.e. plant habit and invasion ability). Overall, this study emphasizes the need to continue generating and analyzing genome size data in order to puzzle out the evolution of this parameter and its many biological correlates

Clean optical spectrum of the radio jet of 3C 120

We present integral field spectroscopy (IFS) of the central region of 3C 120. We have modeled the nuclear and host galaxy 3D spectra using techniques normally applied to imaging, decoupling both components, and obtained a residual datacube. Using this residual datacube, we detected the extended emission line region associated with the radio jet. We obtained, for the first time, a clean spectrum of this region and found compelling evidences of a jet-cloud interaction. The jet compresses and splits the gas cloud which is ionized by the AGN and/or by the strong local UV photon field generated by a shock process. We cannot confirm the detection of an extended emission line region associated with the counter-jet reported by Axon (1989).Comment: 13 pages, 3 figures, accepted for publishing in Ap

Seasonal prediction of the boreal winter stratosphere

The predictability of the Northern Hemisphere stratosphere and its underlying dynamics are investigated in five state-of-the-art seasonal prediction systems from the Copernicus Climate Change Service (C3S) multi-model database. Special attention is devoted to the connection between the stratospheric polar vortex (SPV) and lower-stratosphere wave activity (LSWA). We find that in winter (December to February) dynamical forecasts initialised on the first of November are considerably more skilful than empirical forecasts based on October anomalies. Moreover, the coupling of the SPV with mid-latitude LSWA (i.e., meridional eddy heat flux) is generally well reproduced by the forecast systems, allowing for the identification of a robust link between the predictability of wave activity above the tropopause and the SPV skill. Our results highlight the importance of November-to-February LSWA, in particular in the Eurasian sector, for forecasts of the winter stratosphere. Finally, the role of potential sources of seasonal stratospheric predictability is considered: we find that the C3S multi-model overestimates the stratospheric response to El Niño–Southern Oscillation (ENSO) and underestimates the influence of the Quasi–Biennial Oscillation (QBO)

Gain-switched semiconductor lasers with pulsed excitation and optical injection for dual-comb spectroscopy

In this work we demonstrate the capability of two gain-switched optically injected semiconductor lasers to perform high-resolution dual-comb spectroscopy. The use of low duty cycle pulse trains to gain switch the lasers, combined with optical injection, allows us to obtain flat-topped optical frequency combs with 350 optical lines (within 10 dB) spaced by 100 MHz. These frequency combs significantly improve the spectral resolution reported so far on dual-comb spectroscopy with gain-switched laser diodes. We evaluate the performance of our system by measuring the transmission profile of an absorption line of H13CN at the C-band, analyzing the attainable signal-to-noise ratio for a range of averaging times

Integral Field Spectroscopy of the Central Regions of 3C 120: Evidence of a Past Merging Event

IFS combined with HST WFPC imaging were used to characterize the central regions of the Seyfert 1 radio galaxy 3C 120. We carried out the analysis of the data, deriving intensity maps of different emission lines and the continua at different wavelengths from the observed spectra. Applying a 2D modeling to the HST images we decoupled the nucleus and the host galaxy, and analyzed the host morphology. The host is a highly distorted bulge dominated galaxy, rich in substructures. We developed a new technique to model the IFS data extending the 2D modeling. Using this technique we separated the Seyfert nucleus and the host galaxy spectra, and derived a residual data cube with spectral and spatial information of the different structures in 3C 120. Three continuum-dominated structures (named A, B, and C) and other three extended emission line regions (EELRs, named E1, E2 and E3) are found in 3C 120 which does not follow the general behavior of a bulge dominated galaxy. We also found shells in the central kpc that may be remnants of a past merging event in this galaxy. The origin of E1 is most probably due to the interaction of the radio-jet of 3C 120 with the intergalactic medium. Structures A, B, and the shell at the southeast of the nucleus seem to correspond to a larger morphological clumpy structure that may be a tidal tail, consequence of the past merging event. We found a bright EELR (E2) in the innermost part of this tidal tail, nearby the nucleus, which shows a high ionization level. The kinematics of the E2 region and its connection to the tidal tail suggest that the tail has channeled gas from the outer regions to the center.Comment: 55 pages, 18 figures and 5 tables Accepted by AP

UHPLC-HRMS (Orbitrap) fingerprinting in the classification and authentication of cranberry-based natural products and pharmaceuticals using multivariate calibration methods

UHPLC-HRMS (Orbitrap) fingerprinting in negative and positive H-ESI mode was applied to the characterization, classification and authentication of cranberry-based natural and pharmaceutical products. HRMS data in full scan mode (m/z 100-1500) at a resolution of 70,000 full-width at half maximum was recorded and processed with MSConvert software to obtain a profile of peak intensities in function of m/z values and retention times. A threshold peak filter of absolute intensity (105 counts) was applied to reduce data complexity. Principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) revealed patterns able to discriminate the analyzed samples according to the fruit of origin (cranberry, grape, blueberry and raspberry). Discrimination among cranberry-based natural and cranberry-based pharmaceutical preparations was also achieved. Both, UHPLC-HRMS fingerprints in negative and positive H-ESI modes, as well as the data fusion of both acquisition modes, showed to be good chemical descriptors to address cranberry extracts authentication. Validation of the proposed methodology showed a prediction rate of 100% of the samples. Obtained data was further treated by partial least squares (PLS) regression to identify frauds and quantify the percentage of adulterant fruits in cranberry-fruit extracts, achieving prediction errors in the range 0.17-3.86%