Vision-Based Production of Personalized Video

In this paper we present a novel vision-based system for the automated production of personalised video souvenirs for visitors in leisure and cultural heritage venues. Visitors are visually identified and tracked through a camera network. The system produces a personalized DVD souvenir at the end of a visitor’s stay allowing visitors to relive their experiences. We analyze how we identify visitors by fusing facial and body features, how we track visitors, how the tracker recovers from failures due to occlusions, as well as how we annotate and compile the final product. Our experiments demonstrate the feasibility of the proposed approach

Psicopatología en el paciente atópico, funcionamiento familiar y calidad de vida del cuidador

Abstract. Generating meaningful digests of videos by extracting interesting frames remains a difficult task. In this paper, we define interesting events as unusual events which occur rarely in the entire video and we propose a novel interesting event summarization framework based on the technique of density ratio estimation recently introduced in machine learning. Our proposed framework is unsupervised and it can be applied to general video sources, including videos from moving cameras. We evaluated the proposed approach on a publicly available dataset in the context of anomalous crowd behavior and with a challenging personal video dataset. We demonstrated competitive performance both in accuracy relative to human annotation and computation time

Multimodal and ontology-based fusion approaches of audio and visual processing for violence detection in movies

In this paper we present our research results towards the detection of violent scenes in movies, employing advanced fusion methodologies, based on learning, knowledge representation and reasoning. Towards this goal, a multi-step approach is followed: initially, automated audio and visual analysis is performed to extract audio and visual cues. Then, two different fusion approaches are deployed: (i) a multimodal one that provides binary decisions on the existence of violence or not, employing machine learning techniques, (ii) an ontological and reasoning one, that combines the audio-visual cues with violence and multimedia ontologies. The latter reasons out not only the existence of violence or not in a video scene, but also the type of violence (fight, screams, gunshots). Both approaches are experimentally tested, validated and compared for the binary decision problem of violence detection. Finally, results for the violence type identification are presented for the ontological fusion approach. For evaluation purposes, a large dataset of real movie data has been populated. © 2011 Elsevier Ltd. All rights reserved

A Novel “Trouserslike” Technique for the Extraction of 22-Year-Old Pacemaker Leads

Cardiac management devices have become an integral part of our armament for treatment of heart diseases. However, complications may arise that mandate extraction of either the device or the lead. The noninterventional lead extraction has become a topic of avid debate as simple traction is associated with low success rates whereas laser-assisted extraction carries a high economic cost. Herein we present a case of 22-year-old pacemaker leads extracted with a novel “trouserslike technique” that could present an attractive alternative for leads implanted for more than 10 years when laser sheaths are not accessible. © 2018 The Society of Thoracic Surgeon

Propranolol Versus Metoprolol for Treatment of Electrical Storm in Patients With Implantable Cardioverter-Defibrillator

Background: Electrical storm (ES), characterized by unrelenting recurrences of ventricular arrhythmias, is observed in approximately 30% of patients with implantable cardioverter-defibrillators (ICDs) and is associated with high mortality rates. Objectives: Sympathetic blockade with β-blockers, usually in combination with intravenous (IV) amiodarone, have proved highly effective in the suppression of ES. In this study, we compared the efficacy of a nonselective β-blocker (propranolol) versus a β1-selective blocker (metoprolol) in the management of ES. Methods: Between 2011 and 2016, 60 ICD patients (45 men, mean age 65.0 ± 8.5 years) with ES developed within 24 h from admission were randomly assigned to therapy with either propranolol (160 mg/24 h, Group A) or metoprolol (200 mg/24 h, Group B), combined with IV amiodarone for 48 h. Results: Patients under propranolol therapy in comparison with metoprolol-treated individuals presented a 2.67 times decreased incidence rate (incidence rate ratio: 0.375; 95% confidence interval: 0.207 to 0.678; p = 0.001) of ventricular arrhythmic events (tachycardia or fibrillation) and a 2.34 times decreased rate of ICD discharges (incidence rate ratio: 0.428; 95% CI: 0.227 to 0.892; p = 0.004) during the intensive care unit (ICU) stay, after adjusting for age, sex, ejection fraction, New York Heart Association functional class, heart failure type, arrhythmia type, and arrhythmic events before ICU admission. At the end of the first 24-h treatment period, 27 of 30 (90.0%) patients in group A, while only 16 of 30 (53.3%) patients in group B were free of arrhythmic events (p = 0.03). The termination of arrhythmic events was 77.5% less likely in Group B compared with Group A (hazard ratio: 0.225; 95% CI: 0.112 to 0.453; p < 0.001). Time to arrhythmia termination and length of hospital stay were significantly shorter in the propranolol group (p < 0.05 for both). Conclusions: The combination of IV amiodarone and oral propranolol is safe, effective, and superior to the combination of IV amiodarone and oral metoprolol in the management of ES in ICD patients. © 2018 American College of Cardiology Foundatio