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	Author	R. Clariso; David Masip; A. Rius
	Title	Student projects empowering mobile learning in higher education			Type	Journal
	Year	2014	Publication	Revista de Universidad y Sociedad del Conocimiento	Abbreviated Journal	RUSC
	Volume	11	Issue		Pages	192-207
	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	1698-580X	ISBN		Medium
	Area		Expedition		Conference
	Notes	OR;MV			Approved	no
	Call Number	Admin @ si @ CMR2014			Serial	2619
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	Author	Joan Arnedo-Moreno; D. Bañeres; Xavier Baro; S. Caballe; S. Guerrero; L. Porta; J. Prieto
	Title	Va-ID: A trust-based virtual assessment system			Type	Conference Article
	Year	2014	Publication	6th International Conference on Intelligent Networking and Collaborative Systems	Abbreviated Journal
	Volume		Issue		Pages	328 - 335
	Keywords
	Abstract	Even though online education is a very important pillar of lifelong education, institutions are still reluctant to wager for a fully online educational model. At the end, they keep relying on on-site assessment systems, mainly because fully virtual alternatives do not have the deserved social recognition or credibility. Thus, the design of virtual assessment systems that are able to provide effective proof of student authenticity and authorship and the integrity of the activities in a scalable and cost efficient manner would be very helpful. This paper presents ValID, a virtual assessment approach based on a continuous trust level evaluation between students and the institution. The current trust level serves as the main mechanism to dynamically decide which kind of controls a given student should be subjected to, across different courses in a degree. The main goal is providing a fair trade-off between security, scalability and cost, while maintaining the perceived quality of the educational model.
	Address	Salerna; Italy; September 2014
	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	978-1-4799-6386-7	Medium
	Area		Expedition		Conference	INCOS
	Notes	OR; HuPBA;MV			Approved	no
	Call Number	Admin @ si @ ABB2014			Serial	2620
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	Author	B. Zhou; Agata Lapedriza; J. Xiao; A. Torralba; A. Oliva
	Title	Learning Deep Features for Scene Recognition using Places Database			Type	Conference Article
	Year	2014	Publication	28th Annual Conference on Neural Information Processing Systems	Abbreviated Journal
	Volume		Issue		Pages	487-495
	Keywords
	Abstract
	Address	Montreal; Canada; December 2014
	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	NIPS
	Notes	OR;MV			Approved	no
	Call Number	Admin @ si @ ZLX2014			Serial	2621
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	Author	Agata Lapedriza; David Masip; David 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
	Title	Figure-ground segregation: A fully nonlocal approach			Type	Journal Article
	Year	2016	Publication	Vision Research	Abbreviated Journal	VR
	Volume	126	Issue		Pages	308-317
	Keywords	Figure-ground segregation; Nonlocal approach; Directional linear voting; Nonlinear diffusion
	Abstract	We present a computational model that computes and integrates in a nonlocal fashion several configural cues for automatic figure-ground segregation. Our working hypothesis is that the figural status of each pixel is a nonlocal function of several geometric shape properties and it can be estimated without explicitly relying on object boundaries. The methodology is grounded on two elements: multi-directional linear voting and nonlinear diffusion. A first estimation of the figural status of each pixel is obtained as a result of a voting process, in which several differently oriented line-shaped neighborhoods vote to express their belief about the figural status of the pixel. A nonlinear diffusion process is then applied to enforce the coherence of figural status estimates among perceptually homogeneous regions. Computer simulations fit human perception and match the experimental evidence that several cues cooperate in defining figure-ground segregation. The results of this work suggest that figure-ground segregation involves feedback from cells with larger receptive fields in higher visual cortical areas.
	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	Admin @ si @ Dim2016b			Serial	2623
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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	Youssef El Rhabi; Simon Loic; Brun Luc
	Title	Estimation de la pose d’une caméra à partir d’un flux vidéo en s’approchant du temps réel			Type	Conference Article
	Year	2015	Publication	15ème édition d'ORASIS, journées francophones des jeunes chercheurs en vision par ordinateur ORASIS2015	Abbreviated Journal
	Volume		Issue		Pages
	Keywords	Augmented Reality; SFM; SLAM; real time pose computation; 2D/3D registration
	Abstract	Finding a way to estimate quickly and robustly the pose of an image is essential in augmented reality. Here we will discuss the approach we chose in order to get closer to real time by using SIFT points [4]. We propose a method based on filtering both SIFT points and images on which to focus on. Hence we will focus on relevant data.
	Address	Amiens; France; June 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	ORASIS
	Notes	DAG; 600.077			Approved	no
	Call Number	Admin @ si @ RLL2015			Serial	2626
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	Author	Bogdan Raducanu; Alireza Bosaghzadeh; Fadi Dornaika
	Title	Multi-observation Face Recognition in Videos based on Label Propagation			Type	Conference Article
	Year	2015	Publication	6th Workshop on Analysis and Modeling of Faces and Gestures AMFG2015	Abbreviated Journal
	Volume		Issue		Pages	10-17
	Keywords
	Abstract	In order to deal with the huge amount of content generated by social media, especially for indexing and retrieval purposes, the focus shifted from single object recognition to multi-observation object recognition. Of particular interest is the problem of face recognition (used as primary cue for persons’ identity assessment), since it is highly required by popular social media search engines like Facebook and Youtube. Recently, several approaches for graph-based label propagation were proposed. However, the associated graphs were constructed in an ad-hoc manner (e.g., using the KNN graph) that cannot cope properly with the rapid and frequent changes in data appearance, a phenomenon intrinsically related with video sequences. In this paper, we propose a novel approach for efficient and adaptive graph construction, based on a two-phase scheme: (i) the first phase is used to adaptively find the neighbors of a sample and also to find the adequate weights for the minimization function of the second phase; (ii) in the second phase, the selected neighbors along with their corresponding weights are used to locally and collaboratively estimate the sparse affinity matrix weights. Experimental results performed on Honda Video Database (HVDB) and a subset of video sequences extracted from the popular TV-series ’Friends’ show a distinct advantage of the proposed method over the existing standard graph construction methods.
	Address	Boston; USA; June 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	CVPRW
	Notes	LAMP; 600.068; 600.072;			Approved	no
	Call Number	Admin @ si @ RBD2015			Serial	2627
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	Author	Marco Pedersoli; Andrea Vedaldi; Jordi Gonzalez; Xavier Roca
	Title	A coarse-to-fine approach for fast deformable object detection			Type	Journal Article
	Year	2015	Publication	Pattern Recognition	Abbreviated Journal	PR
	Volume	48	Issue	5	Pages	1844-1853
	Keywords
	Abstract	We present a method that can dramatically accelerate object detection with part based models. The method is based on the observation that the cost of detection is likely to be dominated by the cost of matching each part to the image, and not by the cost of computing the optimal configuration of the parts as commonly assumed. Therefore accelerating detection requires minimizing the number of part-to-image comparisons. To this end we propose a multiple-resolutions hierarchical part based model and a corresponding coarse-to-fine inference procedure that recursively eliminates from the search space unpromising part placements. The method yields a ten-fold speedup over the standard dynamic programming approach and is complementary to the cascade-of-parts approach of [9]. Compared to the latter, our method does not have parameters to be determined empirically, which simplifies its use during the training of the model. Most importantly, the two techniques can be combined to obtain a very significant speedup, of two orders of magnitude in some cases. We evaluate our method extensively on the PASCAL VOC and INRIA datasets, demonstrating a very high increase in the detection speed with little degradation of the accuracy.
	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; 600.078; 602.005; 605.001; 302.012			Approved	no
	Call Number	Admin @ si @ PVG2015			Serial	2628
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	Author	M. Cruz; Cristhian A. Aguilera-Carrasco; Boris X. Vintimilla; Ricardo Toledo; Angel Sappa
	Title	Cross-spectral image registration and fusion: an evaluation study			Type	Conference Article
	Year	2015	Publication	2nd International Conference on Machine Vision and Machine Learning	Abbreviated Journal
	Volume		Issue		Pages
	Keywords	multispectral imaging; image registration; data fusion; infrared and visible spectra
	Abstract	This paper presents a preliminary study on the registration and fusion of cross-spectral imaging. The objective is to evaluate the validity of widely used computer vision approaches when they are applied at different spectral bands. In particular, we are interested in merging images from the infrared (both long wave infrared: LWIR and near infrared: NIR) and visible spectrum (VS). Experimental results with different data sets are presented.
	Address	Barcelona; July 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	MVML
	Notes	ADAS; 600.076			Approved	no
	Call Number	Admin @ si @ CAV2015			Serial	2629
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	Author	Cristhian A. Aguilera-Carrasco; Angel Sappa; Ricardo Toledo
	Title	LGHD: a Feature Descriptor for Matching Across Non-Linear Intensity Variations			Type	Conference Article
	Year	2015	Publication	22th IEEE International Conference on Image Processing	Abbreviated Journal
	Volume		Issue		Pages	178 - 181
	Keywords
	Abstract
	Address	Quebec; Canada; September 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	ICIP
	Notes	ADAS; 600.076			Approved	no
	Call Number	Admin @ si @ AST2015			Serial	2630
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	Author	Jiaolong Xu
	Title	Domain Adaptation of Deformable Part-based Models			Type	Book Whole
	Year	2015	Publication	PhD Thesis, Universitat Autonoma de Barcelona-CVC	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract	On-board pedestrian detection is crucial for Advanced Driver Assistance Systems (ADAS). An accurate classication is fundamental for vision-based pedestrian detection. The underlying assumption for learning classiers is that the training set and the deployment environment (testing) follow the same probability distribution regarding the features used by the classiers. However, in practice, there are dierent reasons that can break this constancy assumption. Accordingly, reusing existing classiers by adapting them from the previous training environment (source domain) to the new testing one (target domain) is an approach with increasing acceptance in the computer vision community. In this thesis we focus on the domain adaptation of deformable part-based models (DPMs) for pedestrian detection. As a prof of concept, we use a computer graphic based synthetic dataset, i.e. a virtual world, as the source domain, and adapt the virtual-world trained DPM detector to various real-world dataset. We start by exploiting the maximum detection accuracy of the virtual-world trained DPM. Even though, when operating in various real-world datasets, the virtualworld trained detector still suer from accuracy degradation due to the domain gap of virtual and real worlds. We then focus on domain adaptation of DPM. At the rst step, we consider single source and single target domain adaptation and propose two batch learning methods, namely A-SSVM and SA-SSVM. Later, we further consider leveraging multiple target (sub-)domains for progressive domain adaptation and propose a hierarchical adaptive structured SVM (HA-SSVM) for optimization. Finally, we extend HA-SSVM for the challenging online domain adaptation problem, aiming at making the detector to automatically adapt to the target domain online, without any human intervention. All of the proposed methods in this thesis do not require revisiting source domain data. The evaluations are done on the Caltech pedestrian detection benchmark. Results show that SA-SSVM slightly outperforms A-SSVM and avoids accuracy drops as high as 15 points when comparing with a non-adapted detector. The hierarchical model learned by HA-SSVM further boosts the domain adaptation performance. Finally, the online domain adaptation method has demonstrated that it can achieve comparable accuracy to the batch learned models while not requiring manually label target domain examples. Domain adaptation for pedestrian detection is of paramount importance and a relatively unexplored area. We humbly hope the work in this thesis could provide foundations for future work in this area.
	Address	April 2015
	Corporate Author				Thesis	Ph.D. thesis
	Publisher		Place of Publication		Editor	Antonio Lopez
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-84-943427-1-4	Medium
	Area		Expedition		Conference
	Notes	ADAS; 600.076			Approved	no
	Call Number	Admin @ si @ Xu2015			Serial	2631
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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	Olivier Penacchio; Xavier Otazu; A. wilkins; J. Harris
	Title	Uncomfortable images prevent lateral interactions in the cortex from providing a sparse code			Type	Conference Article
	Year	2015	Publication	European Conference on Visual Perception ECVP2015	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	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;			Approved	no
	Call Number	Admin @ si @ POW2015			Serial	2633
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	Author	Xavier Otazu; Olivier Penacchio; Xim Cerda-Company
	Title	An excitatory-inhibitory firing rate model accounts for brightness induction, colour induction and visual discomfort			Type	Conference Article
	Year	2015	Publication	Barcelona Computational, Cognitive and Systems Neuroscience	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	Address	Barcelona; June 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	BARCCSYN
	Notes	NEUROBIT;			Approved	no
	Call Number	Admin @ si @ OPC2015b			Serial	2634
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