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	Author	Fernando Vilariño; Panagiota Spyridonos; Petia Radeva; Jordi Vitria; Fernando Azpiroz; Juan Malagelada
	Title	Device, system and method for measurement and analysis of contractile activity			Type	Patent
	Year	2009	Publication	US 2009/0202117 A1	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract	A method and system for determining intestinal dysfunction condition are provided by classifying and analyzing image frames captured in-vivo. The method and system also relate to the detection of contractile activity in intestinal tracts, to automatic detection of video image frames taken in the gastrointestinal tract including contractile activity, and more particularly to measurement and analysis of contractile activity of the GI tract based on image intensity of in vivo image data.
	Address	Pearl Cohen Zedek Latzer
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area	800	Expedition		Conference
	Notes	MV;OR;MILAB;SIAI			Approved	no
	Call Number	IAM @ iam @ VSR2009			Serial	1704
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	Author	Panagiota Spyridonos; Fernando Vilariño; Jordi Vitria; Petia Radeva; Fernando Azpiroz; Juan Malagelada
	Title	Device, system and method for automatic detection of contractile activity in an image frame			Type	Patent
	Year	2011	Publication	US 2011/0044515 A1	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract	A device, system and method for automatic detection of contractile activity of a body lumen in an image frame is provided, wherein image frames during contractile activity are captured and/or image frames including contractile activity are automatically detected, such as through pattern recognition and/or feature extraction to trace image frames including contractions, e.g., with wrinkle patterns. A manual procedure of annotation of contractions, e.g. tonic contractions in capsule endoscopy, may consist of the visualization of the whole video by a specialist, and the labeling of the contraction frames. Embodiments of the present invention may be suitable for implementation in an in vivo imaging system.
	Address	Pearl Cohen Zedek Latzer, LLP, 1500 Broadway 12th Floor, New York (NY) 10036 (US)
	Corporate Author	US Patent Office			Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	MV;OR;MILAB;SIAI			Approved	no
	Call Number	IAM @ iam @ SVV2011			Serial	1701
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	Author	Marc Sunset Perez; Marc Comino Trinidad; Dimosthenis Karatzas; Antonio Chica Calaf; Pere Pau Vazquez Alcocer
	Title	Development of general‐purpose projection‐based augmented reality systems			Type	Journal
	Year	2016	Publication	IADIs international journal on computer science and information systems	Abbreviated Journal	IADIs
	Volume	11	Issue	2	Pages	1-18
	Keywords
	Abstract	Despite the large amount of methods and applications of augmented reality, there is little homogenizatio n on the software platforms that support them. An exception may be the low level control software that is provided by some high profile vendors such as Qualcomm and Metaio. However, these provide fine grain modules for e.g. element tracking. We are more co ncerned on the application framework, that includes the control of the devices working together for the development of the AR experience. In this paper we describe the development of a software framework for AR setups. We concentrate on the modular design of the framework, but also on some hard problems such as the calibration stage, crucial for projection – based AR. The developed framework is suitable and has been tested in AR applications using camera – projector pairs, for both fixed and nomadic setups
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	DAG; 600.084			Approved	no
	Call Number	Admin @ si @ SCK2016			Serial	2890
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	Author	Carles Fernandez; Pau Baiget; Xavier Roca; Jordi Gonzalez
	Title	Determining the Best Suited Semantic Events for Cognitive Surveillance			Type	Journal Article
	Year	2011	Publication	Expert Systems with Applications	Abbreviated Journal	EXSY
	Volume	38	Issue	4	Pages	4068–4079
	Keywords	Cognitive surveillance; Event modeling; Content-based video retrieval; Ontologies; Advanced user interfaces
	Abstract	State-of-the-art systems on cognitive surveillance identify and describe complex events in selected domains, thus providing end-users with tools to easily access the contents of massive video footage. Nevertheless, as the complexity of events increases in semantics and the types of indoor/outdoor scenarios diversify, it becomes difficult to assess which events describe better the scene, and how to model them at a pixel level to fulfill natural language requests. We present an ontology-based methodology that guides the identification, step-by-step modeling, and generalization of the most relevant events to a specific domain. Our approach considers three steps: (1) end-users provide textual evidence from surveilled video sequences; (2) transcriptions are analyzed top-down to build the knowledge bases for event description; and (3) the obtained models are used to generalize event detection to different image sequences from the surveillance domain. This framework produces user-oriented knowledge that improves on existing advanced interfaces for video indexing and retrieval, by determining the best suited events for video understanding according to end-users. We have conducted experiments with outdoor and indoor scenes showing thefts, chases, and vandalism, demonstrating the feasibility and generalization of this proposal.
	Address
	Corporate Author				Thesis
	Publisher	Elsevier	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	ISE			Approved	no
	Call Number	Admin @ si @ FBR2011a			Serial	1722
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	Author	V. Valev; Petia Radeva
	Title	Determining structural descriptions by boolean formulas advances in structural and syntactic Pattern Recognition.			Type	Miscellaneous
	Year	1992	Publication	Proceeding of the International Workshop on Structural and Syntactic Pattern Recognition. Ed. Bunke, World Scientific Pub.	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	MILAB			Approved	no
	Call Number	BCNPCL @ bcnpcl @ VaR1992a			Serial	251
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	Author	V. Valev; Petia Radeva
	Title	Determining Structural Description by Boolean Formulas.			Type	Book Chapter
	Year	1992	Publication	Advances in Structural and Syntactic Pattern Recognition	Abbreviated Journal
	Volume	5	Issue		Pages	131–140
	Keywords
	Abstract	Pattern recognition is an active area of research with many applications, some of which have reached commercial maturity. Structural and syntactic methods are very powerful. They are based on symbolic data structures together with matching, parsing, and reasoning procedures that are able to infer interpretations of complex input patterns. This book gives an overview of the latest developments and achievements in the field.
	Address
	Corporate Author				Thesis
	Publisher	World Scientific	Place of Publication		Editor	H. Bunke
	Language		Summary Language		Original Title
	Series Editor		Series Title	Machine Perception and Artificial Intelligence:	Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-981-279-791-9	Medium
	Area		Expedition		Conference
	Notes	MILAB			Approved	no
	Call Number	BCNPCL @ bcnpcl @ VaR1992c			Serial	254
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	Author	David Guillamet; Jordi Vitria
	Title	Determining a Suitable Metric when using Non-negative Matrix Factorization.			Type	Miscellaneous
	Year	2002	Publication	IEEE International Conference on Pattern Recognition, 2: 128–131.	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	Address	Quebec, Canada
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	OR;MV			Approved	no
	Call Number	BCNPCL @ bcnpcl @ GVi2002			Serial	294
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	Author	Michael Teutsch; Angel Sappa; Riad I. Hammoud
	Title	Detection, Classification, and Tracking			Type	Book Chapter
	Year	2022	Publication	Computer Vision in the Infrared Spectrum. Synthesis Lectures on Computer Vision	Abbreviated Journal
	Volume		Issue		Pages	35-58
	Keywords
	Abstract	Automatic image and video exploitation or content analysis is a technique to extract higher-level information from a scene such as objects, behavior, (inter-)actions, environment, or even weather conditions. The relevant information is assumed to be contained in the two-dimensional signal provided in an image (width and height in pixels) or the three-dimensional signal provided in a video (width, height, and time). But also intermediate-level information such as object classes [196], locations [197], or motion [198] can help applications to fulfill certain tasks such as intelligent compression [199], video summarization [200], or video retrieval [201]. Usually, videos with their temporal dimension are a richer source of data compared to single images [202] and thus certain video content can be extracted from videos only such as object motion or object behavior. Often, machine learning or nowadays deep learning techniques are utilized to model prior knowledge about object or scene appearance using labeled training samples [203, 204]. After a learning phase, these models are then applied in real world applications, which is called inference.
	Address
	Corporate Author				Thesis
	Publisher	Springer	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	SLCV
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-3-031-00698-2	Medium
	Area		Expedition		Conference
	Notes	MSIAU; MACO			Approved	no
	Call Number	Admin @ si @ TSH2022c			Serial	3806
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	Author	Santiago Segui; Michal Drozdzal; Ekaterina Zaytseva; Fernando Azpiroz; Petia Radeva; Jordi Vitria
	Title	Detection of wrinkle frames in endoluminal videos using betweenness centrality measures for images			Type	Journal Article
	Year	2014	Publication	IEEE Transactions on Information Technology in Biomedicine	Abbreviated Journal	TITB
	Volume	18	Issue	6	Pages	1831-1838
	Keywords	Wireless Capsule Endoscopy; Small Bowel Motility Dysfunction; Contraction Detection; Structured Prediction; Betweenness Centrality
	Abstract	Intestinal contractions are one of the most important events to diagnose motility pathologies of the small intestine. When visualized by wireless capsule endoscopy (WCE), the sequence of frames that represents a contraction is characterized by a clear wrinkle structure in the central frames that corresponds to the folding of the intestinal wall. In this paper we present a new method to robustly detect wrinkle frames in full WCE videos by using a new mid-level image descriptor that is based on a centrality measure proposed for graphs. We present an extended validation, carried out in a very large database, that shows that the proposed method achieves state of the art performance for this task.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	OR; MILAB; 600.046;MV			Approved	no
	Call Number	Admin @ si @ SDZ2014			Serial	2385
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	Author	Xavier Otazu; M. Ribo; M. Peracaula; J.M. Paredes; J. Nuñez
	Title	Detection of superimposed periodic signals using wavelets			Type	Journal
	Year	2002	Publication	Monthly Notices of the Royal Astronomical Society, 333, 2: 365–372 (IF: 4.671)	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	CIC			Approved	no
	Call Number	CAT @ cat @ ORP2002			Serial	272
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	Author	Diana Ramirez Cifuentes; Ana Freire; Ricardo Baeza Yates; Joaquim Punti Vidal; Pilar Medina Bravo; Diego Velazquez; Josep M. Gonfaus; Jordi Gonzalez
	Title	Detection of Suicidal Ideation on Social Media: Multimodal, Relational, and Behavioral Analysis			Type	Journal Article
	Year	2020	Publication	Journal of Medical Internet Research	Abbreviated Journal	JMIR
	Volume	22	Issue	7	Pages	e17758
	Keywords
	Abstract	Background: Suicide risk assessment usually involves an interaction between doctors and patients. However, a significant number of people with mental disorders receive no treatment for their condition due to the limited access to mental health care facilities; the reduced availability of clinicians; the lack of awareness; and stigma, neglect, and discrimination surrounding mental disorders. In contrast, internet access and social media usage have increased significantly, providing experts and patients with a means of communication that may contribute to the development of methods to detect mental health issues among social media users. Objective: This paper aimed to describe an approach for the suicide risk assessment of Spanish-speaking users on social media. We aimed to explore behavioral, relational, and multimodal data extracted from multiple social platforms and develop machine learning models to detect users at risk. Methods: We characterized users based on their writings, posting patterns, relations with other users, and images posted. We also evaluated statistical and deep learning approaches to handle multimodal data for the detection of users with signs of suicidal ideation (suicidal ideation risk group). Our methods were evaluated over a dataset of 252 users annotated by clinicians. To evaluate the performance of our models, we distinguished 2 control groups: users who make use of suicide-related vocabulary (focused control group) and generic random users (generic control group). Results: We identified significant statistical differences between the textual and behavioral attributes of each of the control groups compared with the suicidal ideation risk group. At a 95% CI, when comparing the suicidal ideation risk group and the focused control group, the number of friends (P=.04) and median tweet length (P=.04) were significantly different. The median number of friends for a focused control user (median 578.5) was higher than that for a user at risk (median 372.0). Similarly, the median tweet length was higher for focused control users, with 16 words against 13 words of suicidal ideation risk users. Our findings also show that the combination of textual, visual, relational, and behavioral data outperforms the accuracy of using each modality separately. We defined text-based baseline models based on bag of words and word embeddings, which were outperformed by our models, obtaining an increase in accuracy of up to 8% when distinguishing users at risk from both types of control users. Conclusions: The types of attributes analyzed are significant for detecting users at risk, and their combination outperforms the results provided by generic, exclusively text-based baseline models. After evaluating the contribution of image-based predictive models, we believe that our results can be improved by enhancing the models based on textual and relational features. These methods can be extended and applied to different use cases related to other mental disorders.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	ISE; 600.098; 600.119			Approved	no
	Call Number	Admin @ si @ RFB2020			Serial	3552
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	Author	Antonio Lopez; Cristina Cañero; Joan Serrat; J. Saludes; Felipe Lumbreras; T. Graf
	Title	Detection of lane markings based on ridgeness and RANSAC			Type	Miscellaneous
	Year	2005	Publication	Proceedings of the 8th International IEEE Conference on Intelligent Transportation Systems, 733–738	Abbreviated Journal
	Volume		Issue		Pages
	Keywords	lane markings
	Abstract
	Address	Vienna (Austria)
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	ADAS			Approved	no
	Call Number	ADAS @ adas @ LCS2005			Serial	588
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	Author	Jose Elias Yauri; M. Lagos; H. Vega-Huerta; P. de-la-Cruz; G.L.E Maquen-Niño; E. Condor-Tinoco
	Title	Detection of Epileptic Seizures Based-on Channel Fusion and Transformer Network in EEG Recordings			Type	Journal Article
	Year	2023	Publication	International Journal of Advanced Computer Science and Applications	Abbreviated Journal	IJACSA
	Volume	14	Issue	5	Pages	1067-1074
	Keywords	Epilepsy; epilepsy detection; EEG; EEG channel fusion; convolutional neural network; self-attention
	Abstract	According to the World Health Organization, epilepsy affects more than 50 million people in the world, and specifically, 80% of them live in developing countries. Therefore, epilepsy has become among the major public issue for many governments and deserves to be engaged. Epilepsy is characterized by uncontrollable seizures in the subject due to a sudden abnormal functionality of the brain. Recurrence of epilepsy attacks change people’s lives and interferes with their daily activities. Although epilepsy has no cure, it could be mitigated with an appropriated diagnosis and medication. Usually, epilepsy diagnosis is based on the analysis of an electroencephalogram (EEG) of the patient. However, the process of searching for seizure patterns in a multichannel EEG recording is a visual demanding and time consuming task, even for experienced neurologists. Despite the recent progress in automatic recognition of epilepsy, the multichannel nature of EEG recordings still challenges current methods. In this work, a new method to detect epilepsy in multichannel EEG recordings is proposed. First, the method uses convolutions to perform channel fusion, and next, a self-attention network extracts temporal features to classify between interictal and ictal epilepsy states. The method was validated in the public CHB-MIT dataset using the k-fold cross-validation and achieved 99.74% of specificity and 99.15% of sensitivity, surpassing current approaches.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	IAM			Approved	no
	Call Number	Admin @ si @			Serial	3856
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	Author	Sergio Escalera; Oriol Pujol; Petia Radeva
	Title	Detection of Complex Salient Regions			Type	Journal
	Year	2008	Publication	EURASIP Journal on Advances in Signal Processing, vol. 2008, article ID451389, 11 pages	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	MILAB;HuPBA			Approved	no
	Call Number	BCNPCL @ bcnpcl @ EPR2008b			Serial	960
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	Author	Ivan Huerta; Michael Holte; Thomas B. Moeslund; Jordi Gonzalez
	Title	Detection and Removal of Chromatic Moving Shadows in Surveillance Scenarios			Type	Conference Article
	Year	2009	Publication	12th International Conference on Computer Vision	Abbreviated Journal
	Volume		Issue		Pages	1499 - 1506
	Keywords
	Abstract	Segmentation in the surveillance domain has to deal with shadows to avoid distortions when detecting moving objects. Most segmentation approaches dealing with shadow detection are typically restricted to penumbra shadows. Therefore, such techniques cannot cope well with umbra shadows. Consequently, umbra shadows are usually detected as part of moving objects. In this paper we present a novel technique based on gradient and colour models for separating chromatic moving cast shadows from detected moving objects. Firstly, both a chromatic invariant colour cone model and an invariant gradient model are built to perform automatic segmentation while detecting potential shadows. In a second step, regions corresponding to potential shadows are grouped by considering “a bluish effect” and an edge partitioning. Lastly, (i) temporal similarities between textures and (ii) spatial similarities between chrominance angle and brightness distortions are analysed for all potential shadow regions in order to finally identify umbra shadows. Unlike other approaches, our method does not make any a-priori assumptions about camera location, surface geometries, surface textures, shapes and types of shadows, objects, and background. Experimental results show the performance and accuracy of our approach in different shadowed materials and illumination conditions.
	Address	Kyoto, Japan
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	1550-5499	ISBN	978-1-4244-4420-5	Medium
	Area		Expedition		Conference	ICCV
	Notes				Approved	no
	Call Number	ISE @ ise @ HHM2009			Serial	1213
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