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Maedeh Aghaei; Mariella Dimiccoli; C. Canton-Ferrer; Petia Radeva |
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Title |
Towards social pattern characterization from egocentric photo-streams |
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Journal Article |
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Year |
2018 |
Publication |
Computer Vision and Image Understanding |
Abbreviated Journal |
CVIU |
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171 |
Issue ![sorted by Issue field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
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104-117 |
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Keywords |
Social pattern characterization; Social signal extraction; Lifelogging; Convolutional and recurrent neural networks |
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Following the increasingly popular trend of social interaction analysis in egocentric vision, this article presents a comprehensive pipeline for automatic social pattern characterization of a wearable photo-camera user. The proposed framework relies merely on the visual analysis of egocentric photo-streams and consists of three major steps. The first step is to detect social interactions of the user where the impact of several social signals on the task is explored. The detected social events are inspected in the second step for categorization into different social meetings. These two steps act at event-level where each potential social event is modeled as a multi-dimensional time-series, whose dimensions correspond to a set of relevant features for each task; finally, LSTM is employed to classify the time-series. The last step of the framework is to characterize social patterns of the user. Our goal is to quantify the duration, the diversity and the frequency of the user social relations in various social situations. This goal is achieved by the discovery of recurrences of the same people across the whole set of social events related to the user. Experimental evaluation over EgoSocialStyle – the proposed dataset in this work, and EGO-GROUP demonstrates promising results on the task of social pattern characterization from egocentric photo-streams. |
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MILAB; no proj |
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Admin @ si @ ADC2018 |
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3022 |
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Mireia Forns-Nadal; Federico Sem; Anna Mane; Laura Igual; Dani Guinart; Oscar Vilarroya |
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Title |
Increased Nucleus Accumbens Volume in First-Episode Psychosis |
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Journal Article |
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2017 |
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Psychiatry Research-Neuroimaging |
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PRN |
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263 |
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57-60 |
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Nucleus accumbens has been reported as a key structure in the neurobiology of schizophrenia. Studies analyzing structural abnormalities have shown conflicting results, possibly related to confounding factors. We investigated the nucleus accumbens volume using manual delimitation in first-episode psychosis (FEP) controlling for age, cannabis use and medication. Thirty-one FEP subjects who were naive or minimally exposed to antipsychotics and a control group were MRI scanned and clinically assessed from baseline to 6 months of follow-up. FEP showed increased relative and total accumbens volumes. Clinical correlations with negative symptoms, duration of untreated psychosis and cannabis use were not significant. |
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MILAB; no menciona |
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Admin @ si @ FSM2017 |
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3028 |
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Marc Bolaños; Alvaro Peris; Francisco Casacuberta; Sergi Solera; Petia Radeva |
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Title |
Egocentric video description based on temporally-linked sequences |
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Journal Article |
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2018 |
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Journal of Visual Communication and Image Representation |
Abbreviated Journal |
JVCIR |
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50 |
Issue ![sorted by Issue field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
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205-216 |
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egocentric vision; video description; deep learning; multi-modal learning |
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Egocentric vision consists in acquiring images along the day from a first person point-of-view using wearable cameras. The automatic analysis of this information allows to discover daily patterns for improving the quality of life of the user. A natural topic that arises in egocentric vision is storytelling, that is, how to understand and tell the story relying behind the pictures.
In this paper, we tackle storytelling as an egocentric sequences description problem. We propose a novel methodology that exploits information from temporally neighboring events, matching precisely the nature of egocentric sequences. Furthermore, we present a new method for multimodal data fusion consisting on a multi-input attention recurrent network. We also release the EDUB-SegDesc dataset. This is the first dataset for egocentric image sequences description, consisting of 1,339 events with 3,991 descriptions, from 55 days acquired by 11 people. Finally, we prove that our proposal outperforms classical attentional encoder-decoder methods for video description. |
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MILAB; no proj |
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Admin @ si @ BPC2018 |
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3109 |
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Author |
Mariella Dimiccoli; Cathal Gurrin; David J. Crandall; Xavier Giro; Petia Radeva |
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Title |
Introduction to the special issue: Egocentric Vision and Lifelogging |
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Journal Article |
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2018 |
Publication |
Journal of Visual Communication and Image Representation |
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JVCIR |
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55 |
Issue ![sorted by Issue field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
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352-353 |
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MILAB; no proj |
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Admin @ si @ DGC2018 |
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3187 |
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Author |
Sumit K. Banchhor; Narendra D. Londhe; Tadashi Araki; Luca Saba; Petia Radeva; Narendra N. Khanna; Jasjit S. Suri |
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Title |
Calcium detection, its quantification, and grayscale morphology-based risk stratification using machine learning in multimodality big data coronary and carotid scans: A review. |
Type |
Journal Article |
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Year |
2018 |
Publication |
Computers in Biology and Medicine |
Abbreviated Journal |
CBM |
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101 |
Issue ![sorted by Issue field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
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184-198 |
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Heart disease; Stroke; Atherosclerosis; Intravascular; Coronary; Carotid; Calcium; Morphology; Risk stratification |
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Abstract |
Purpose of review
Atherosclerosis is the leading cause of cardiovascular disease (CVD) and stroke. Typically, atherosclerotic calcium is found during the mature stage of the atherosclerosis disease. It is therefore often a challenge to identify and quantify the calcium. This is due to the presence of multiple components of plaque buildup in the arterial walls. The American College of Cardiology/American Heart Association guidelines point to the importance of calcium in the coronary and carotid arteries and further recommend its quantification for the prevention of heart disease. It is therefore essential to stratify the CVD risk of the patient into low- and high-risk bins.
Recent finding
Calcium formation in the artery walls is multifocal in nature with sizes at the micrometer level. Thus, its detection requires high-resolution imaging. Clinical experience has shown that even though optical coherence tomography offers better resolution, intravascular ultrasound still remains an important imaging modality for coronary wall imaging. For a computer-based analysis system to be complete, it must be scientifically and clinically validated. This study presents a state-of-the-art review (condensation of 152 publications after examining 200 articles) covering the methods for calcium detection and its quantification for coronary and carotid arteries, the pros and cons of these methods, and the risk stratification strategies. The review also presents different kinds of statistical models and gold standard solutions for the evaluation of software systems useful for calcium detection and quantification. Finally, the review concludes with a possible vision for designing the next-generation system for better clinical outcomes. |
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MILAB; no proj |
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no |
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Admin @ si @ BLA2018 |
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3188 |
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Permanent link to this record |