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	Author	Antonio Lopez; J. Hilgenstock; A. Busse; Ramon Baldrich; Felipe Lumbreras; Joan Serrat
	Title	Temporal Coherence Analysis for Intelligent Headlight Control			Type	Miscellaneous
	Year	2008	Publication	2nd Workshop on Perception, Planning and Navigation for Intelligent Vehicles	Abbreviated Journal
	Volume		Issue		Pages	59–64
	Keywords	Intelligent Headlights
	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	IROS
	Notes	ADAS;CIC			Approved	no
	Call Number	ADAS @ adas @ LHB2008b			Serial	1112
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	Author	Carlo Gatta; Simone Balocco; Francesco Ciompi; R. Hemetsberger; O. Rodriguez-Leor; Petia Radeva
	Title	Real-time gating of IVUS sequences based on motion blur analysis: Method and quantitative validation			Type	Conference Article
	Year	2010	Publication	13th international conference on Medical image computing and computer-assisted intervention	Abbreviated Journal
	Volume	II	Issue		Pages	59-67
	Keywords
	Abstract	Intravascular Ultrasound (IVUS) is an image-guiding technique for cardiovascular diagnostic, providing cross-sectional images of vessels. During the acquisition, the catheter is pulled back (pullback) at a constant speed in order to acquire spatially subsequent images of the artery. However, during this procedure, the heart twist produces a swinging fluctuation of the probe position along the vessel axis. In this paper we propose a real-time gating algorithm based on the analysis of motion blur variations during the IVUS sequence. Quantitative tests performed on an in-vitro ground truth data base shown that our method is superior to state of the art algorithms both in computational speed and accuracy.
	Address
	Corporate Author				Thesis
	Publisher	Springer-Verlag Berlin	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	MICCAI
	Notes	MILAB			Approved	no
	Call Number	BCNPCL @ bcnpcl @ GBC2010			Serial	1447
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	Author	Debora Gil; Jaume Garcia; Ruth Aris; Guillaume Houzeaux; Manuel Vazquez
	Title	A Riemmanian approach to cardiac fiber architecture modelling			Type	Conference Article
	Year	2009	Publication	1st International Conference on Mathematical & Computational Biomedical Engineering	Abbreviated Journal
	Volume		Issue		Pages	59-62
	Keywords	cardiac fiber architecture; diffusion tensor magnetic resonance imaging; differential (Rie- mannian) geometry.
	Abstract	There is general consensus that myocardial fiber architecture should be modelled in order to fully understand the electromechanical properties of the Left Ventricle (LV). Diffusion Tensor magnetic resonance Imaging (DTI) is the reference image modality for rapid measurement of fiber orientations by means of the tensor principal eigenvectors. In this work, we present a mathematical framework for across subject comparison of the local geometry of the LV anatomy including the fiber architecture from the statistical analysis of DTI studies. We use concepts of differential geometry for defining a parametric domain suitable for statistical analysis of a low number of samples. We use Riemannian metrics to define a consistent computation of DTI principal eigenvector modes of variation. Our framework has been applied to build an atlas of the LV fiber architecture from 7 DTI normal canine hearts.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication	Swansea (UK)	Editor	Nithiarasu, R.L.R.V.L.
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	CMBE
	Notes	IAM			Approved	no
	Call Number	IAM @ iam @ FGA2009			Serial	1520
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	Author	Nataliya Shapovalova; Wenjuan Gong; Marco Pedersoli; Xavier Roca; Jordi Gonzalez
	Title	On Importance of Interactions and Context in Human Action Recognition			Type	Conference Article
	Year	2011	Publication	5th Iberian Conference on Pattern Recognition and Image Analysis	Abbreviated Journal
	Volume	6669	Issue		Pages	58-66
	Keywords
	Abstract	This paper is focused on the automatic recognition of human events in static images. Popular techniques use knowledge of the human pose for inferring the action, and the most recent approaches tend to combine pose information with either knowledge of the scene or of the objects with which the human interacts. Our approach makes a step forward in this direction by combining the human pose with the scene in which the human is placed, together with the spatial relationships between humans and objects. Based on standard, simple descriptors like HOG and SIFT, recognition performance is enhanced when these three types of knowledge are taken into account. Results obtained in the PASCAL 2010 Action Recognition Dataset demonstrate that our technique reaches state-of-the-art results using simple descriptors and classifiers.
	Address	Las Palmas de Gran Canaria. Spain
	Corporate Author				Thesis
	Publisher	Springer Berlin Heidelberg	Place of Publication		Editor	J. Vitria, J.M. Sanches, and M. Hernandez
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN	0302-9743	ISBN	978-3-642-21256-7	Medium
	Area		Expedition		Conference	IbPRIA
	Notes	ISE			Approved	no
	Call Number	Admin @ si @ SGP2011			Serial	1750
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	Author	Fei Yang; Yaxing Wang; Luis Herranz; Yongmei Cheng; Mikhail Mozerov
	Title	A Novel Framework for Image-to-image Translation and Image Compression			Type	Journal Article
	Year	2022	Publication	Neurocomputing	Abbreviated Journal	NEUCOM
	Volume	508	Issue		Pages	58-70
	Keywords
	Abstract	Data-driven paradigms using machine learning are becoming ubiquitous in image processing and communications. In particular, image-to-image (I2I) translation is a generic and widely used approach to image processing problems, such as image synthesis, style transfer, and image restoration. At the same time, neural image compression has emerged as a data-driven alternative to traditional coding approaches in visual communications. In this paper, we study the combination of these two paradigms into a joint I2I compression and translation framework, focusing on multi-domain image synthesis. We first propose distributed I2I translation by integrating quantization and entropy coding into an I2I translation framework (i.e. I2Icodec). In practice, the image compression functionality (i.e. autoencoding) is also desirable, requiring to deploy alongside I2Icodec a regular image codec. Thus, we further propose a unified framework that allows both translation and autoencoding capabilities in a single codec. Adaptive residual blocks conditioned on the translation/compression mode provide flexible adaptation to the desired functionality. The experiments show promising results in both I2I translation and image compression using a single model.
	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	LAMP			Approved	no
	Call Number	Admin @ si @ YWH2022			Serial	3679
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	Author	Jose Manuel Alvarez; Theo Gevers; Antonio Lopez
	Title	3D Scene Priors for Road Detection			Type	Conference Article
	Year	2010	Publication	23rd IEEE Conference on Computer Vision and Pattern Recognition	Abbreviated Journal
	Volume		Issue		Pages	57–64
	Keywords	road detection
	Abstract	Vision-based road detection is important in different areas of computer vision such as autonomous driving, car collision warning and pedestrian crossing detection. However, current vision-based road detection methods are usually based on low-level features and they assume structured roads, road homogeneity, and uniform lighting conditions. Therefore, in this paper, contextual 3D information is used in addition to low-level cues. Low-level photometric invariant cues are derived from the appearance of roads. Contextual cues used include horizon lines, vanishing points, 3D scene layout and 3D road stages. Moreover, temporal road cues are included. All these cues are sensitive to different imaging conditions and hence are considered as weak cues. Therefore, they are combined to improve the overall performance of the algorithm. To this end, the low-level, contextual and temporal cues are combined in a Bayesian framework to classify road sequences. Large scale experiments on road sequences show that the road detection method is robust to varying imaging conditions, road types, and scenarios (tunnels, urban and highway). Further, using the combined cues outperforms all other individual cues. Finally, the proposed method provides highest road detection accuracy when compared to state-of-the-art methods.
	Address	San Francisco; CA; USA; June 2010
	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	1063-6919	ISBN	978-1-4244-6984-0	Medium
	Area		Expedition		Conference	CVPR
	Notes	ADAS;ISE			Approved	no
	Call Number	ADAS @ adas @ AGL2010a			Serial	1302
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	Author	Enric Marti; Debora Gil; Carme Julia
	Title	Experiencia d aplicació de la metodología d aprenentatge per proyectes en assignatures d Enginyeria Informàtica per a una millor adaptació als crèdits ECTS i EEES			Type	Miscellaneous
	Year	2008	Publication	Experiències docents innovadores de la UAB en ciències experimentals i tecnologies i en ciències de la salud	Abbreviated Journal
	Volume	1	Issue		Pages	57-68
	Keywords
	Abstract
	Address
	Corporate Author				Thesis
	Publisher	UAB	Place of Publication		Editor	IDES-UAB; M.Enric Martinez, E.A.
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-84-490-2576-1	Medium
	Area		Expedition		Conference
	Notes	IAM;ADAS;			Approved	no
	Call Number	IAM @ iam @ MGJ2008			Serial	1592
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	Author	Aura Hernandez-Sabate; Meritxell Joanpere; Nuria Gorgorio; Lluis Albarracin
	Title	Mathematics learning opportunities when playing a Tower Defense Game			Type	Journal
	Year	2015	Publication	International Journal of Serious Games	Abbreviated Journal	IJSG
	Volume	2	Issue	4	Pages	57-71
	Keywords	Tower Defense game; learning opportunities; mathematics; problem solving; game design
	Abstract	A qualitative research study is presented herein with the purpose of identifying mathematics learning opportunities in students between 10 and 12 years old while playing a commercial version of a Tower Defense game. These learning opportunities are understood as mathematicisable moments of the game and involve the establishment of relationships between the game and mathematical problem solving. Based on the analysis of these mathematicisable moments, we conclude that the game can promote problem-solving processes and learning opportunities that can be associated with different mathematical contents that appears in mathematics curricula, thought it seems that teacher or new game elements might be needed to facilitate the processes.
	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	ADAS; 600.076			Approved	no
	Call Number	Admin @ si @ HJG2015			Serial	2730
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	Author	Mireia Forns-Nadal; Federico Sem; Anna Mane; Laura Igual; Dani Guinart; Oscar Vilarroya
	Title	Increased Nucleus Accumbens Volume in First-Episode Psychosis			Type	Journal Article
	Year	2017	Publication	Psychiatry Research-Neuroimaging	Abbreviated Journal	PRN
	Volume	263	Issue		Pages	57-60
	Keywords
	Abstract	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.
	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; no menciona			Approved	no
	Call Number	Admin @ si @ FSM2017			Serial	3028
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	Author	Meysam Madadi; Hugo Bertiche; Wafa Bouzouita; Isabelle Guyon; Sergio Escalera
	Title	Learning Cloth Dynamics: 3D+Texture Garment Reconstruction Benchmark			Type	Conference Article
	Year	2021	Publication	Proceedings of Machine Learning Research	Abbreviated Journal
	Volume	133	Issue		Pages	57-76
	Keywords
	Abstract	Human avatars are important targets in many computer applications. Accurately tracking, capturing, reconstructing and animating the human body, face and garments in 3D are critical for human-computer interaction, gaming, special effects and virtual reality. In the past, this has required extensive manual animation. Regardless of the advances in human body and face reconstruction, still modeling, learning and analyzing human dynamics need further attention. In this paper we plan to push the research in this direction, e.g. understanding human dynamics in 2D and 3D, with special attention to garments. We provide a large-scale dataset (more than 2M frames) of animated garments with variable topology and type, calledCLOTH3D++. The dataset contains RGBA video sequences paired with its corresponding 3D data. We pay special care to garment dynamics and realistic rendering of RGB data, including lighting, fabric type and texture. With this dataset, we hold a competition at NeurIPS2020. We design three tracks so participants can compete to develop the best method to perform 3D garment reconstruction in a sequence from (1) 3D-to-3D garments, (2) RGB-to-3D garments, and (3) RGB-to-3D garments plus texture. We also provide a baseline method, based on graph convolutional networks, for each track. Baseline results show that there is a lot of room for improvements. However, due to the challenging nature of the problem, no participant could outperform the baselines.
	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	HUPBA; no proj			Approved	no
	Call Number	Admin @ si @ MBB2021			Serial	3655
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	Author	Pierluigi Casale; Oriol Pujol; Petia Radeva
	Title	Face-to-face social activity detection using data collected with a wearable device			Type	Conference Article
	Year	2009	Publication	4th Iberian Conference on Pattern Recognition and Image Analysis	Abbreviated Journal
	Volume	5524	Issue		Pages	56–63
	Keywords
	Abstract	In this work the feasibility of building a socially aware badge that learns from user activities is explored. A wearable multisensor device has been prototyped for collecting data about user movements and photos of the environment where the user acts. Using motion data, speaking and other activities have been classified. Images have been analysed in order to complement motion data and help for the detection of social behaviours. A face detector and an activity classifier are both used for detecting if users have a social activity in the time they worn the device. Good results encourage the improvement of the system at both hardware and software level
	Address	Póvoa de Varzim, Portugal
	Corporate Author				Thesis
	Publisher	Springer Berlin Heidelberg	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN	0302-9743	ISBN	978-3-642-02171-8	Medium
	Area		Expedition		Conference	IbPRIA
	Notes	MILAB;HuPBA			Approved	no
	Call Number	BCNPCL @ bcnpcl @ CPR2009b			Serial	1206
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	Author	Marçal Rusiñol; Josep Llados
	Title	The Role of the Users in Handwritten Word Spotting Applications: Query Fusion and Relevance Feedback			Type	Conference Article
	Year	2012	Publication	13th International Conference on Frontiers in Handwriting Recognition	Abbreviated Journal
	Volume		Issue		Pages	55-60
	Keywords
	Abstract	In this paper we present the importance of including the user in the loop in a handwritten word spotting framework. Several off-the-shelf query fusion and relevance feedback strategies have been tested in the handwritten word spotting context. The increase in terms of precision when the user is included in the loop is assessed using two datasets of historical handwritten documents and a baseline word spotting approach based on a bag-of-visual-words model.
	Address	Bari, Italy
	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	978-1-4673-2262-1	Medium
	Area		Expedition		Conference	ICFHR
	Notes	DAG			Approved	no
	Call Number	Admin @ si @ RuL2012			Serial	2054
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	Author	Agata Lapedriza; David Masip; D.Sanchez
	Title	Emotions Classification using Facial Action Units Recognition			Type	Conference Article
	Year	2014	Publication	17th International Conference of the Catalan Association for Artificial Intelligence	Abbreviated Journal
	Volume	269	Issue		Pages	55-64
	Keywords
	Abstract	In this work we build a system for automatic emotion classification from image sequences. We analyze subtle changes in facial expressions by detecting a subset of 12 representative facial action units (AUs). Then, we classify emotions based on the output of these AUs classifiers, i.e. the presence/absence of AUs. We base the AUs classification upon a set of spatio-temporal geometric and appearance features for facial representation, fusing them within the emotion classifier. A decision tree is trained for emotion classifying, making the resulting model easy to interpret by capturing the combination of AUs activation that lead to a particular emotion. For Cohn-Kanade database, the proposed system classifies 7 emotions with a mean accuracy of near 90%, attaining a similar recognition accuracy in comparison with non-interpretable models that are not based in AUs detection.
	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	978-1-61499-451-0	Medium
	Area		Expedition		Conference	CCIA
	Notes	OR;MV			Approved	no
	Call Number	Admin @ si @ LMS2014			Serial	2622
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	Author	Mariella Dimiccoli; Marc Bolaños; Estefania Talavera; Maedeh Aghaei; Stavri G. Nikolov; Petia Radeva
	Title	SR-Clustering: Semantic Regularized Clustering for Egocentric Photo Streams Segmentation			Type	Journal Article
	Year	2017	Publication	Computer Vision and Image Understanding	Abbreviated Journal	CVIU
	Volume	155	Issue		Pages	55-69
	Keywords
	Abstract	While wearable cameras are becoming increasingly popular, locating relevant information in large unstructured collections of egocentric images is still a tedious and time consuming processes. This paper addresses the problem of organizing egocentric photo streams acquired by a wearable camera into semantically meaningful segments. First, contextual and semantic information is extracted for each image by employing a Convolutional Neural Networks approach. Later, by integrating language processing, a vocabulary of concepts is defined in a semantic space. Finally, by exploiting the temporal coherence in photo streams, images which share contextual and semantic attributes are grouped together. The resulting temporal segmentation is particularly suited for further analysis, ranging from activity and event recognition to semantic indexing and summarization. Experiments over egocentric sets of nearly 17,000 images, show that the proposed approach outperforms state-of-the-art methods.
	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; 601.235			Approved	no
	Call Number	Admin @ si @ DBT2017			Serial	2714
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	Author	Mireia Sole; Joan Blanco; Debora Gil; G. Fonseka; Richard Frodsham; Oliver Valero; Francesca Vidal; Zaida Sarrate
	Title	Is there a pattern of Chromosome territoriality along mice spermatogenesis?			Type	Conference Article
	Year	2017	Publication	3rd Spanish MeioNet Meeting Abstract Book	Abbreviated Journal
	Volume		Issue		Pages	55-56
	Keywords
	Abstract
	Address	Miraflores de la Sierra; Madrid; June 2017
	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	MEIONET
	Notes	IAM; 600.096; 600.145			Approved	no
	Call Number	Admin @ si @			Serial	2958
Permanent link to this record