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	Author	Arash Akbarinia; C. Alejandro Parraga
	Title	Biologically Plausible Colour Naming Model			Type	Conference Article
	Year	2015	Publication	European Conference on Visual Perception ECVP2015	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract	Poster
	Address	Liverpool; UK; August 2015
	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	ECVP
	Notes	NEUROBIT; 600.068			Approved	no
	Call Number	Admin @ si @ AkP2015			Serial	2660
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	Author	Jorge Bernal; F. Javier Sanchez; Cristina Rodriguez de Miguel; Gloria Fernandez Esparrach
	Title	Bulding up the future of colonoscopy: A synergy between clinicians and computer scientists			Type	Book Chapter
	Year	2015	Publication	Colonoscopy and Colorectal Cancer	Abbreviated Journal
	Volume		Issue		Pages
	Keywords	Intelligent systems; Image properties; Validation; Clinical drawbacks; Endoluminal scene description
	Abstract	Recent advances in endoscopic technology have generated an increasing interest in strengthening the collaboration between clinicians and computers scientist to develop intelligent systems that can provide additional information to clinicians in the different stages of an intervention. The objective of this chapter is to identify clinical drawbacks of colonoscopy in order to define potential areas of collaboration. Once areas are defined, we present the challenges that colonoscopy images present in order computational methods to provide with meaningful output, including those related to image formation and acquisition, as they are proven to have an impact in the performance of an intelligent system. Finally, we also propose how to define validation frameworks in order to assess the performance of a given method, making an special emphasis on how databases should be created and annotated and which metrics should be used to evaluate systems correctly.
	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	978-953-51-2225-8	Medium
	Area		Expedition		Conference
	Notes	MV			Approved	no
	Call Number	Admin @ si @ BSR2015			Serial	2624
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	Author	Chen Zhang; Maria del Mar Vila Muñoz; Petia Radeva; Roberto Elosua; Maria Grau; Angels Betriu; Elvira Fernandez-Giraldez; Laura Igual
	Title	Carotid Artery Segmentation in Ultrasound Images			Type	Conference Article
	Year	2015	Publication	Computing and Visualization for Intravascular Imaging and Computer Assisted Stenting (CVII-STENT2015), Joint MICCAI Workshops	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	Address	Munich; Germany; October 2015
	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	CVII-STENT
	Notes	MILAB			Approved	no
	Call Number	Admin @ si @ ZVR2015			Serial	2675
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	Author	Antoni Gurgui; Debora Gil; Enric Marti
	Title	Laplacian Unitary Domain for Texture Morphing			Type	Conference Article
	Year	2015	Publication	Proceedings of the 10th International Conference on Computer Vision Theory and Applications VISIGRAPP2015	Abbreviated Journal
	Volume	1	Issue		Pages	693-699
	Keywords	Facial; metamorphosis;LaplacianMorphing
	Abstract	Deformation of expressive textures is the gateway to realistic computer synthesis of expressions. By their good mathematical properties and flexible formulation on irregular meshes, most texture mappings rely on solutions to the Laplacian in the cartesian space. In the context of facial expression morphing, this approximation can be seen from the opposite point of view by neglecting the metric. In this paper, we use the properties of the Laplacian in manifolds to present a novel approach to warping expressive facial images in order to generate a morphing between them.
	Address	Munich; Germany; February 2015
	Corporate Author				Thesis
	Publisher	SciTePress	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-989-758-089-5	Medium
	Area		Expedition		Conference	VISAPP
	Notes	IAM; 600.075			Approved	no
	Call Number	Admin @ si @ GGM2015			Serial	2614
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	Author	Xavier Otazu; Olivier Penacchio; Xim Cerda-Company
	Title	Brightness and colour induction through contextual influences in V1			Type	Conference Article
	Year	2015	Publication	Scottish Vision Group 2015 SGV2015	Abbreviated Journal
	Volume	12	Issue	9	Pages	1208-2012
	Keywords
	Abstract
	Address	Carnoustie; Scotland; March 2015
	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	SGV
	Notes	NEUROBIT;			Approved	no
	Call Number	Admin @ si @ OPC2015a			Serial	2632
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	Author	David Sanchez-Mendoza; David Masip; Agata Lapedriza
	Title	Emotion recognition from mid-level features			Type	Journal Article
	Year	2015	Publication	Pattern Recognition Letters	Abbreviated Journal	PRL
	Volume	67	Issue	Part 1	Pages	66–74
	Keywords	Facial expression; Emotion recognition; Action units; Computer vision
	Abstract	In this paper we present a study on the use of Action Units as mid-level features for automatically recognizing basic and subtle emotions. We propose a representation model based on mid-level facial muscular movement features. We encode these movements dynamically using the Facial Action Coding System, and propose to use these intermediate features based on Action Units (AUs) to classify emotions. AUs activations are detected fusing a set of spatiotemporal geometric and appearance features. The algorithm is validated in two applications: (i) the recognition of 7 basic emotions using the publicly available Cohn-Kanade database, and (ii) the inference of subtle emotional cues in the Newscast database. In this second scenario, we consider emotions that are perceived cumulatively in longer periods of time. In particular, we Automatically classify whether video shoots from public News TV channels refer to Good or Bad news. To deal with the different video lengths we propose a Histogram of Action Units and compute it using a sliding window strategy on the frame sequences. Our approach achieves accuracies close to human perception.
	Address
	Corporate Author				Thesis
	Publisher	Elsevier B.V.	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	0167-8655	ISBN		Medium
	Area		Expedition		Conference
	Notes	OR;MV			Approved	no
	Call Number	Admin @ si @ SML2015			Serial	2746
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	Author	Marçal Rusiñol; Dimosthenis Karatzas; Josep Llados
	Title	Automatic Verification of Properly Signed Multi-page Document Images			Type	Conference Article
	Year	2015	Publication	Proceedings of the Eleventh International Symposium on Visual Computing	Abbreviated Journal
	Volume	9475	Issue		Pages	327-336
	Keywords	Document Image; Manual Inspection; Signature Verification; Rejection Criterion; Document Flow
	Abstract	In this paper we present an industrial application for the automatic screening of incoming multi-page documents in a banking workflow aimed at determining whether these documents are properly signed or not. The proposed method is divided in three main steps. First individual pages are classified in order to identify the pages that should contain a signature. In a second step, we segment within those key pages the location where the signatures should appear. The last step checks whether the signatures are present or not. Our method is tested in a real large-scale environment and we report the results when checking two different types of real multi-page contracts, having in total more than 14,500 pages.
	Address	Las Vegas, Nevada, USA; December 2015
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume	9475	Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	ISVC
	Notes	DAG; 600.077			Approved	no
	Call Number	Admin @ si @			Serial	3189
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	Author	Carles Sanchez; Oriol Ramos Terrades; Patricia Marquez; Enric Marti; J.Roncaries; Debora Gil
	Title	Automatic evaluation of practices in Moodle for Self Learning in Engineering			Type	Journal
	Year	2015	Publication	Journal of Technology and Science Education	Abbreviated Journal	JOTSE
	Volume	5	Issue	2	Pages	97-106
	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	IAM; DAG; 600.075; 600.077			Approved	no
	Call Number	Admin @ si @ SRM2015			Serial	2610
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	Author	Enric Marti; J.Roncaries; Debora Gil; Aura Hernandez-Sabate; Antoni Gurgui; Ferran Poveda
	Title	PBL On Line: A proposal for the organization, part-time monitoring and assessment of PBL group activities			Type	Journal
	Year	2015	Publication	Journal of Technology and Science Education	Abbreviated Journal	JOTSE
	Volume	5	Issue	2	Pages	87-96
	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	IAM; ADAS; 600.076; 600.075			Approved	no
	Call Number	Admin @ si @ MRG2015			Serial	2608
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	Author	Alvaro Cepero; Albert Clapes; Sergio Escalera
	Title	Automatic non-verbal communication skills analysis: a quantitative evaluation			Type	Journal Article
	Year	2015	Publication	AI Communications	Abbreviated Journal	AIC
	Volume	28	Issue	1	Pages	87-101
	Keywords	Social signal processing; human behavior analysis; multi-modal data description; multi-modal data fusion; non-verbal communication analysis; e-Learning
	Abstract	The oral communication competence is defined on the top of the most relevant skills for one's professional and personal life. Because of the importance of communication in our activities of daily living, it is crucial to study methods to evaluate and provide the necessary feedback that can be used in order to improve these communication capabilities and, therefore, learn how to express ourselves better. In this work, we propose a system capable of evaluating quantitatively the quality of oral presentations in an automatic fashion. The system is based on a multi-modal RGB, depth, and audio data description and a fusion approach in order to recognize behavioral cues and train classifiers able to eventually predict communication quality levels. The performance of the proposed system is tested on a novel dataset containing Bachelor thesis' real defenses, presentations from an 8th semester Bachelor courses, and Master courses' presentations at Universitat de Barcelona. Using as groundtruth the marks assigned by actual instructors, our system achieves high performance categorizing and ranking presentations by their quality, and also making real-valued mark predictions.
	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	0921-7126	ISBN		Medium
	Area		Expedition		Conference
	Notes	HUPBA;MILAB			Approved	no
	Call Number	Admin @ si @ CCE2015			Serial	2549
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	Author	Jordina Torrents-Barrena; Aida Valls; Petia Radeva; Meritxell Arenas; Domenec Puig
	Title	Automatic Recognition of Molecular Subtypes of Breast Cancer in X-Ray images using Segmentation-based Fractal Texture Analysis			Type	Book Chapter
	Year	2015	Publication	Artificial Intelligence Research and Development	Abbreviated Journal
	Volume	277	Issue		Pages	247 - 256
	Keywords
	Abstract	Breast cancer disease has recently been classified into four subtypes regarding the molecular properties of the affected tumor region. For each patient, an accurate diagnosis of the specific type is vital to decide the most appropriate therapy in order to enhance life prospects. Nowadays, advanced therapeutic diagnosis research is focused on gene selection methods, which are not robust enough. Hence, we hypothesize that computer vision algorithms can offer benefits to address the problem of discriminating among them through X-Ray images. In this paper, we propose a novel approach driven by texture feature descriptors and machine learning techniques. First, we segment the tumour part through an active contour technique and then, we perform a complete fractal analysis to collect qualitative information of the region of interest in the feature extraction stage. Finally, several supervised and unsupervised classifiers are used to perform multiclass classification of the aforementioned data. The experimental results presented in this paper support that it is possible to establish a relation between each tumor subtype and the extracted features of the patterns revealed on mammograms.
	Address
	Corporate Author				Thesis
	Publisher	IOS Press	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title	Frontiers in Artificial Intelligence and Applications	Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	MILAB			Approved	no
	Call Number	Admin @ si @TVR2015			Serial	2780
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	Author	Frederic Sampedro; Sergio Escalera; Anna Domenech; Ignasi Carrio
	Title	Automatic Tumor Volume Segmentation in Whole-Body PET/CT Scans: A Supervised Learning Approach Source			Type	Journal Article
	Year	2015	Publication	Journal of Medical Imaging and Health Informatics	Abbreviated Journal	JMIHI
	Volume	5	Issue	2	Pages	192-201
	Keywords	CONTEXTUAL CLASSIFICATION; PET/CT; SUPERVISED LEARNING; TUMOR SEGMENTATION; WHOLE BODY
	Abstract	Whole-body 3D PET/CT tumoral volume segmentation provides relevant diagnostic and prognostic information in clinical oncology and nuclear medicine. Carrying out this procedure manually by a medical expert is time consuming and suffers from inter- and intra-observer variabilities. In this paper, a completely automatic approach to this task is presented. First, the problem is stated and described both in clinical and technological terms. Then, a novel supervised learning segmentation framework is introduced. The segmentation by learning approach is defined within a Cascade of Adaboost classifiers and a 3D contextual proposal of Multiscale Stacked Sequential Learning. Segmentation accuracy results on 200 Breast Cancer whole body PET/CT volumes show mean 49% sensitivity, 99.993% specificity and 39% Jaccard overlap Index, which represent good performance results both at the clinical and technological level.
	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;MILAB			Approved	no
	Call Number	Admin @ si @ SED2015			Serial	2584
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	Author	Wenjuan Gong; W.Zhang; Jordi Gonzalez; Y.Ren; Z.Li
	Title	Enhanced Asymmetric Bilinear Model for Face Recognition			Type	Journal Article
	Year	2015	Publication	International Journal of Distributed Sensor Networks	Abbreviated Journal	IJDSN
	Volume		Issue		Pages	Article ID 218514
	Keywords
	Abstract	Bilinear models have been successfully applied to separate two factors, for example, pose variances and different identities in face recognition problems. Asymmetric model is a type of bilinear model which models a system in the most concise way. But seldom there are works exploring the applications of asymmetric bilinear model on face recognition problem with illumination changes. In this work, we propose enhanced asymmetric model for illumination-robust face recognition. Instead of initializing the factor probabilities randomly, we initialize them with nearest neighbor method and optimize them for the test data. Above that, we update the factor model to be identified. We validate the proposed method on a designed data sample and extended Yale B dataset. The experiment results show that the enhanced asymmetric models give promising results and good recognition accuracies.
	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; 600.063; 600.078			Approved	no
	Call Number	Admin @ si @ GZG2015			Serial	2592
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	Author	Carolina Malagelada; Michal Drozdzal; Santiago Segui; Sara Mendez; Jordi Vitria; Petia Radeva; Javier Santos; Anna Accarino; Juan R. Malagelada; Fernando Azpiroz
	Title	Classification of functional bowel disorders by objective physiological criteria based on endoluminal image analysis			Type	Journal Article
	Year	2015	Publication	American Journal of Physiology-Gastrointestinal and Liver Physiology	Abbreviated Journal	AJPGI
	Volume	309	Issue	6	Pages	G413--G419
	Keywords	capsule endoscopy; computer vision analysis; functional bowel disorders; intestinal motility; machine learning
	Abstract	We have previously developed an original method to evaluate small bowel motor function based on computer vision analysis of endoluminal images obtained by capsule endoscopy. Our aim was to demonstrate intestinal motor abnormalities in patients with functional bowel disorders by endoluminal vision analysis. Patients with functional bowel disorders (n = 205) and healthy subjects (n = 136) ingested the endoscopic capsule (Pillcam-SB2, Given-Imaging) after overnight fast and 45 min after gastric exit of the capsule a liquid meal (300 ml, 1 kcal/ml) was administered. Endoluminal image analysis was performed by computer vision and machine learning techniques to define the normal range and to identify clusters of abnormal function. After training the algorithm, we used 196 patients and 48 healthy subjects, completely naive, as test set. In the test set, 51 patients (26%) were detected outside the normal range (P < 0.001 vs. 3 healthy subjects) and clustered into hypo- and hyperdynamic subgroups compared with healthy subjects. Patients with hypodynamic behavior (n = 38) exhibited less luminal closure sequences (41 ± 2% of the recording time vs. 61 ± 2%; P < 0.001) and more static sequences (38 ± 3 vs. 20 ± 2%; P < 0.001); in contrast, patients with hyperdynamic behavior (n = 13) had an increased proportion of luminal closure sequences (73 ± 4 vs. 61 ± 2%; P = 0.029) and more high-motion sequences (3 ± 1 vs. 0.5 ± 0.1%; P < 0.001). Applying an original methodology, we have developed a novel classification of functional gut disorders based on objective, physiological criteria of small bowel function.
	Address
	Corporate Author				Thesis
	Publisher	American Physiological Society	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; OR;MV			Approved	no
	Call Number	Admin @ si @ MDS2015			Serial	2666
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	Author	Maedeh Aghaei; Mariella Dimiccoli; Petia Radeva
	Title	Towards social interaction detection in egocentric photo-streams			Type	Conference Article
	Year	2015	Publication	Proceedings of SPIE, 8th International Conference on Machine Vision , ICMV 2015	Abbreviated Journal
	Volume	9875	Issue		Pages
	Keywords
	Abstract	Detecting social interaction in videos relying solely on visual cues is a valuable task that is receiving increasing attention in recent years. In this work, we address this problem in the challenging domain of egocentric photo-streams captured by a low temporal resolution wearable camera (2fpm). The major difficulties to be handled in this context are the sparsity of observations as well as unpredictability of camera motion and attention orientation due to the fact that the camera is worn as part of clothing. Our method consists of four steps: multi-faces localization and tracking, 3D localization, pose estimation and analysis of f-formations. By estimating pair-to-pair interaction probabilities over the sequence, our method states the presence or absence of interaction with the camera wearer and specifies which people are more involved in the interaction. We tested our method over a dataset of 18.000 images and we show its reliability on our considered purpose. © (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
	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	ICMV
	Notes	MILAB			Approved	no
	Call Number	Admin @ si @ ADR2015a			Serial	2702
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