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	Author	Aura Hernandez-Sabate; Lluis Albarracin; Daniel Calvo; Nuria Gorgorio
	Title	EyeMath: Identifying Mathematics Problem Solving Processes in a RTS Video Game			Type	Conference Article
	Year	2016	Publication	5th International Conference Games and Learning Alliance	Abbreviated Journal
	Volume	10056	Issue		Pages	50-59
	Keywords	Simulation environment; Automated Driving; Driver-Vehicle interaction
	Abstract	Photorealistic virtual environments are crucial for developing and testing automated driving systems in a safe way during trials. As commercially available simulators are expensive and bulky, this paper presents a low-cost, extendable, and easy-to-use (LEE) virtual environment with the aim to highlight its utility for level 3 driving automation. In particular, an experiment is performed using the presented simulator to explore the influence of different variables regarding control transfer of the car after the system was driving autonomously in a highway scenario. The results show that the speed of the car at the time when the system needs to transfer the control to the human driver is critical.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	GALA
	Notes	ADAS;IAM;			Approved	no
	Call Number	HAC2016			Serial	2864
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	Author	Antonio Hernandez; Sergio Escalera; Stan Sclaroff
	Title	Poselet-basedContextual Rescoring for Human Pose Estimation via Pictorial Structures			Type	Journal Article
	Year	2016	Publication	International Journal of Computer Vision	Abbreviated Journal	IJCV
	Volume	118	Issue	1	Pages	49–64
	Keywords	Contextual rescoring; Poselets; Human pose estimation
	Abstract	In this paper we propose a contextual rescoring method for predicting the position of body parts in a human pose estimation framework. A set of poselets is incorporated in the model, and their detections are used to extract spatial and score-related features relative to other body part hypotheses. A method is proposed for the automatic discovery of a compact subset of poselets that covers the different poses in a set of validation images while maximizing precision. A rescoring mechanism is defined as a set-based boosting classifier that computes a new score for each body joint detection, given its relationship to detections of other body joints and mid-level parts in the image. This new score is incorporated in the pictorial structure model as an additional unary potential, following the recent work of Pishchulin et al. Experiments on two benchmarks show comparable results to Pishchulin et al. while reducing the size of the mid-level representation by an order of magnitude, reducing the execution time by 68 % accordingly.
	Address
	Corporate Author				Thesis
	Publisher	Springer US	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	0920-5691	ISBN		Medium
	Area		Expedition		Conference
	Notes	HuPBA;MILAB;			Approved	no
	Call Number	Admin @ si @ HES2016			Serial	2719
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	Author	Thanh Ha Do; Salvatore Tabbone; Oriol Ramos Terrades
	Title	Sparse representation over learned dictionary for symbol recognition			Type	Journal Article
	Year	2016	Publication	Signal Processing	Abbreviated Journal	SP
	Volume	125	Issue		Pages	36-47
	Keywords	Symbol Recognition; Sparse Representation; Learned Dictionary; Shape Context; Interest Points
	Abstract	In this paper we propose an original sparse vector model for symbol retrieval task. More specically, we apply the K-SVD algorithm for learning a visual dictionary based on symbol descriptors locally computed around interest points. Results on benchmark datasets show that the obtained sparse representation is competitive related to state-of-the-art methods. Moreover, our sparse representation is invariant to rotation and scale transforms and also robust to degraded images and distorted symbols. Thereby, the learned visual dictionary is able to represent instances of unseen classes of symbols.
	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; 600.061; 600.077			Approved	no
	Call Number	Admin @ si @ DTR2016			Serial	2946
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	Author	Egils Avots; M. Daneshmanda; Andres Traumann; Sergio Escalera; G. Anbarjafaria
	Title	Automatic garment retexturing based on infrared information			Type	Journal Article
	Year	2016	Publication	Computers & Graphics	Abbreviated Journal	CG
	Volume	59	Issue		Pages	28-38
	Keywords	Garment Retexturing; Texture Mapping; Infrared Images; RGB-D Acquisition Devices; Shading
	Abstract	This paper introduces a new automatic technique for garment retexturing using a single static image along with the depth and infrared information obtained using the Microsoft Kinect II as the RGB-D acquisition device. First, the garment is segmented out from the image using either the Breadth-First Search algorithm or the semi-automatic procedure provided by the GrabCut method. Then texture domain coordinates are computed for each pixel belonging to the garment using normalised 3D information. Afterwards, shading is applied to the new colours from the texture image. As the main contribution of the proposed method, the latter information is obtained based on extracting a linear map transforming the colour present on the infrared image to that of the RGB colour channels. One of the most important impacts of this strategy is that the resulting retexturing algorithm is colour-, pattern- and lighting-invariant. The experimental results show that it can be used to produce realistic representations, which is substantiated through implementing it under various experimentation scenarios, involving varying lighting intensities and directions. Successful results are accomplished also on video sequences, as well as on images of subjects taking different poses. Based on the Mean Opinion Score analysis conducted on many randomly chosen users, it has been shown to produce more realistic-looking results compared to the existing state-of-the-art methods suggested in the literature. From a wide perspective, the proposed method can be used for retexturing all sorts of segmented surfaces, although the focus of this study is on garment retexturing, and the investigation of the configurations is steered accordingly, since the experiments target an application in the context of virtual fitting rooms.
	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	HuPBA;MILAB;			Approved	no
	Call Number	Admin @ si @ ADT2016			Serial	2759
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	Author	Angel Sappa; Cristhian A. Aguilera-Carrasco; Juan A. Carvajal Ayala; Miguel Oliveira; Dennis Romero; Boris X. Vintimilla; Ricardo Toledo
	Title	Monocular visual odometry: A cross-spectral image fusion based approach			Type	Journal Article
	Year	2016	Publication	Robotics and Autonomous Systems	Abbreviated Journal	RAS
	Volume	85	Issue		Pages	26-36
	Keywords	Monocular visual odometry; LWIR-RGB cross-spectral imaging; Image fusion
	Abstract	This manuscript evaluates the usage of fused cross-spectral images in a monocular visual odometry approach. Fused images are obtained through a Discrete Wavelet Transform (DWT) scheme, where the best setup is empirically obtained by means of a mutual information based evaluation metric. The objective is to have a flexible scheme where fusion parameters are adapted according to the characteristics of the given images. Visual odometry is computed from the fused monocular images using an off the shelf approach. Experimental results using data sets obtained with two different platforms are presented. Additionally, comparison with a previous approach as well as with monocular-visible/infrared spectra are also provided showing the advantages of the proposed scheme.
	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		ISBN		Medium
	Area		Expedition		Conference
	Notes	ADAS;600.086; 600.076			Approved	no
	Call Number	Admin @ si @SAC2016			Serial	2811
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	Author	Alicia Fornes; Josep Llados; Oriol Ramos Terrades; Marçal Rusiñol
	Title	La Visió per Computador com a Eina per a la Interpretació Automàtica de Fonts Documentals			Type	Journal
	Year	2016	Publication	Lligall, Revista Catalana d'Arxivística	Abbreviated Journal
	Volume	39	Issue		Pages	20-46
	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	DAG; 600.097			Approved	no
	Call Number	Admin @ si @ FLR2016			Serial	2897
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	Author	Pedro Martins; Paulo Carvalho; Carlo Gatta
	Title	On the completeness of feature-driven maximally stable extremal regions			Type	Journal Article
	Year	2016	Publication	Pattern Recognition Letters	Abbreviated Journal	PRL
	Volume	74	Issue		Pages	9-16
	Keywords	Local features; Completeness; Maximally Stable Extremal Regions
	Abstract	By definition, local image features provide a compact representation of the image in which most of the image information is preserved. This capability offered by local features has been overlooked, despite being relevant in many application scenarios. In this paper, we analyze and discuss the performance of feature-driven Maximally Stable Extremal Regions (MSER) in terms of the coverage of informative image parts (completeness). This type of features results from an MSER extraction on saliency maps in which features related to objects boundaries or even symmetry axes are highlighted. These maps are intended to be suitable domains for MSER detection, allowing this detector to provide a better coverage of informative image parts. Our experimental results, which were based on a large-scale evaluation, show that feature-driven MSER have relatively high completeness values and provide more complete sets than a traditional MSER detection even when sets of similar cardinality are considered.
	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	LAMP;MILAB;			Approved	no
	Call Number	Admin @ si @ MCG2016			Serial	2748
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	Author	Mohammad Ali Bagheri; Qigang Gao; Sergio Escalera
	Title	Action Recognition by Pairwise Proximity Function Support Vector Machines with Dynamic Time Warping Kernels			Type	Conference Article
	Year	2016	Publication	29th Canadian Conference on Artificial Intelligence	Abbreviated Journal
	Volume	9673	Issue		Pages	3-14
	Keywords
	Abstract	In the context of human action recognition using skeleton data, the 3D trajectories of joint points may be considered as multi-dimensional time series. The traditional recognition technique in the literature is based on time series dis(similarity) measures (such as Dynamic Time Warping). For these general dis(similarity) measures, k-nearest neighbor algorithms are a natural choice. However, k-NN classifiers are known to be sensitive to noise and outliers. In this paper, a new class of Support Vector Machine that is applicable to trajectory classification, such as action recognition, is developed by incorporating an efficient time-series distances measure into the kernel function. More specifically, the derivative of Dynamic Time Warping (DTW) distance measure is employed as the SVM kernel. In addition, the pairwise proximity learning strategy is utilized in order to make use of non-positive semi-definite (PSD) kernels in the SVM formulation. The recognition results of the proposed technique on two action recognition datasets demonstrates the ourperformance of our methodology compared to the state-of-the-art methods. Remarkably, we obtained 89 % accuracy on the well-known MSRAction3D dataset using only 3D trajectories of body joints obtained by Kinect
	Address	Victoria; Canada; May 2016
	Corporate Author				Thesis
	Publisher	Springer International Publishing	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	AI
	Notes	HuPBA;MILAB;			Approved	no
	Call Number	Admin @ si @ BGE2016b			Serial	2770
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	Author	Alvaro Peris; Marc Bolaños; Petia Radeva; Francisco Casacuberta
	Title	Video Description Using Bidirectional Recurrent Neural Networks			Type	Conference Article
	Year	2016	Publication	25th International Conference on Artificial Neural Networks	Abbreviated Journal
	Volume	2	Issue		Pages	3-11
	Keywords	Video description; Neural Machine Translation; Birectional Recurrent Neural Networks; LSTM; Convolutional Neural Networks
	Abstract	Although traditionally used in the machine translation field, the encoder-decoder framework has been recently applied for the generation of video and image descriptions. The combination of Convolutional and Recurrent Neural Networks in these models has proven to outperform the previous state of the art, obtaining more accurate video descriptions. In this work we propose pushing further this model by introducing two contributions into the encoding stage. First, producing richer image representations by combining object and location information from Convolutional Neural Networks and second, introducing Bidirectional Recurrent Neural Networks for capturing both forward and backward temporal relationships in the input frames.
	Address	Barcelona; September 2016
	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	ICANN
	Notes	MILAB;			Approved	no
	Call Number	Admin @ si @ PBR2016			Serial	2833
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	Author	Q. Bao; Marçal Rusiñol; M.Coustaty; Muhammad Muzzamil Luqman; C.D. Tran; Jean-Marc Ogier
	Title	Delaunay triangulation-based features for Camera-based document image retrieval system			Type	Conference Article
	Year	2016	Publication	12th IAPR Workshop on Document Analysis Systems	Abbreviated Journal
	Volume		Issue		Pages	1-6
	Keywords	Camera-based Document Image Retrieval; Delaunay Triangulation; Feature descriptors; Indexing
	Abstract	In this paper, we propose a new feature vector, named DElaunay TRIangulation-based Features (DETRIF), for real-time camera-based document image retrieval. DETRIF is computed based on the geometrical constraints from each pair of adjacency triangles in delaunay triangulation which is constructed from centroids of connected components. Besides, we employ a hashing-based indexing system in order to evaluate the performance of DETRIF and to compare it with other systems such as LLAH and SRIF. The experimentation is carried out on two datasets comprising of 400 heterogeneous-content complex linguistic map images (huge size, 9800 X 11768 pixels resolution)and 700 textual document images.
	Address	Santorini; Greece; April 2016
	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	DAS
	Notes	DAG; 600.061; 600.084; 600.077			Approved	no
	Call Number	Admin @ si @ BRC2016			Serial	2757
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	Author	Sergio Escalera; Vassilis Athitsos; Isabelle Guyon
	Title	Challenges in multimodal gesture recognition			Type	Journal Article
	Year	2016	Publication	Journal of Machine Learning Research	Abbreviated Journal	JMLR
	Volume	17	Issue		Pages	1-54
	Keywords	Gesture Recognition; Time Series Analysis; Multimodal Data Analysis; Computer Vision; Pattern Recognition; Wearable sensors; Infrared Cameras; KinectTM
	Abstract	This paper surveys the state of the art on multimodal gesture recognition and introduces the JMLR special topic on gesture recognition 2011-2015. We began right at the start of the KinectTMrevolution when inexpensive infrared cameras providing image depth recordings became available. We published papers using this technology and other more conventional methods, including regular video cameras, to record data, thus providing a good overview of uses of machine learning and computer vision using multimodal data in this area of application. Notably, we organized a series of challenges and made available several datasets we recorded for that purpose, including tens of thousands of videos, which are available to conduct further research. We also overview recent state of the art works on gesture recognition based on a proposed taxonomy for gesture recognition, discussing challenges and future lines of research.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor	Zhuowen Tu
	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 @ EAG2016			Serial	2764
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	Author	Isabelle Guyon; Imad Chaabane; Hugo Jair Escalante; Sergio Escalera; Damir Jajetic; James Robert Lloyd; Nuria Macia; Bisakha Ray; Lukasz Romaszko; Michele Sebag; Alexander Statnikov; Sebastien Treguer; Evelyne Viegas
	Title	A brief Review of the ChaLearn AutoML Challenge: Any-time Any-dataset Learning without Human Intervention			Type	Conference Article
	Year	2016	Publication	AutoML Workshop	Abbreviated Journal
	Volume		Issue	1	Pages	1-8
	Keywords	AutoML Challenge; machine learning; model selection; meta-learning; repre- sentation learning; active learning
	Abstract	The ChaLearn AutoML Challenge team conducted a large scale evaluation of fully automatic, black-box learning machines for feature-based classification and regression problems. The test bed was composed of 30 data sets from a wide variety of application domains and ranged across different types of complexity. Over six rounds, participants succeeded in delivering AutoML software capable of being trained and tested without human intervention. Although improvements can still be made to close the gap between human-tweaked and AutoML models, this competition contributes to the development of fully automated environments by challenging practitioners to solve problems under specific constraints and sharing their approaches; the platform will remain available for post-challenge submissions at http://codalab.org/AutoML.
	Address	New York; USA; June 2016
	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	ICML
	Notes	HuPBA;MILAB			Approved	no
	Call Number	Admin @ si @ GCE2016			Serial	2769
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	Author	Mohammad Ali Bagheri; Qigang Gao; Sergio Escalera
	Title	Support Vector Machines with Time Series Distance Kernels for Action Classification			Type	Conference Article
	Year	2016	Publication	IEEE Winter Conference on Applications of Computer Vision	Abbreviated Journal
	Volume		Issue		Pages	1-7
	Keywords
	Abstract	Despite the outperformance of Support Vector Machine (SVM) on many practical classification problems, the algorithm is not directly applicable to multi-dimensional trajectories having different lengths. In this paper, a new class of SVM that is applicable to trajectory classification, such as action recognition, is developed by incorporating two efficient time-series distances measures into the kernel function. Dynamic Time Warping and Longest Common Subsequence distance measures along with their derivatives are employed as the SVM kernel. In addition, the pairwise proximity learning strategy is utilized in order to make use of non-positive semi-definite kernels in the SVM formulation. The proposed method is employed for a challenging classification problem: action recognition by depth cameras using only skeleton data; and evaluated on three benchmark action datasets. Experimental results demonstrate the outperformance of our methodology compared to the state-ofthe-art on the considered datasets.
	Address	Lake Placid; NY (USA); March 2016
	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	WACV
	Notes	HuPBA;MILAB;			Approved	no
	Call Number	Admin @ si @ BGE2016a			Serial	2773
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	Author	Angel Sappa; P. Carvajal; Cristhian A. Aguilera-Carrasco; Miguel Oliveira; Dennis Romero; Boris X. Vintimilla
	Title	Wavelet based visible and infrared image fusion: a comparative study			Type	Journal Article
	Year	2016	Publication	Sensors	Abbreviated Journal	SENS
	Volume	16	Issue	6	Pages	1-15
	Keywords	Image fusion; fusion evaluation metrics; visible and infrared imaging; discrete wavelet transform
	Abstract	This paper evaluates different wavelet-based cross-spectral image fusion strategies adopted to merge visible and infrared images. The objective is to find the best setup independently of the evaluation metric used to measure the performance. Quantitative performance results are obtained with state of the art approaches together with adaptations proposed in the current work. The options evaluated in the current work result from the combination of different setups in the wavelet image decomposition stage together with different fusion strategies for the final merging stage that generates the resulting representation. Most of the approaches evaluate results according to the application for which they are intended for. Sometimes a human observer is selected to judge the quality of the obtained results. In the current work, quantitative values are considered in order to find correlations between setups and performance of obtained results; these correlations can be used to define a criteria for selecting the best fusion strategy for a given pair of cross-spectral images. The whole procedure is evaluated with a large set of correctly registered visible and infrared image pairs, including both Near InfraRed (NIR) and Long Wave InfraRed (LWIR).
	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; 600.086; 600.076			Approved	no
	Call Number	Admin @ si @SCA2016			Serial	2807
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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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