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	Author	Aura Hernandez-Sabate; Debora Gil; Jaume Garcia; Enric Marti
	Title	Image-based Cardiac Phase Retrieval in Intravascular Ultrasound Sequences			Type	Journal Article
	Year	2011	Publication	IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control	Abbreviated Journal	T-UFFC
	Volume	58	Issue	1	Pages	60-72
	Keywords	3-D exploring; ECG; band-pass filter; cardiac motion; cardiac phase retrieval; coronary arteries; electrocardiogram signal; image intensity local mean evolution; image-based cardiac phase retrieval; in vivo pullbacks acquisition; intravascular ultrasound sequences; longitudinal motion; signal extrema; time 36 ms; band-pass filters; biomedical ultrasonics; cardiovascular system; electrocardiography; image motion analysis; image retrieval; image sequences; medical image processing; ultrasonic imaging
	Abstract	Longitudinal motion during in vivo pullbacks acquisition of intravascular ultrasound (IVUS) sequences is a major artifact for 3-D exploring of coronary arteries. Most current techniques are based on the electrocardiogram (ECG) signal to obtain a gated pullback without longitudinal motion by using specific hardware or the ECG signal itself. We present an image-based approach for cardiac phase retrieval from coronary IVUS sequences without an ECG signal. A signal reflecting cardiac motion is computed by exploring the image intensity local mean evolution. The signal is filtered by a band-pass filter centered at the main cardiac frequency. Phase is retrieved by computing signal extrema. The average frame processing time using our setup is 36 ms. Comparison to manually sampled sequences encourages a deeper study comparing them to ECG signals.
	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	0885-3010	ISBN		Medium
	Area		Expedition		Conference
	Notes	IAM;ADAS			Approved	no
	Call Number	IAM @ iam @ HGG2011			Serial	1546
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	Author	Koen E.A. van de Sande; Theo Gevers; Cees G.M. Snoek
	Title	Empowering Visual Categorization with the GPU			Type	Journal Article
	Year	2011	Publication	IEEE Transactions on Multimedia	Abbreviated Journal	TMM
	Volume	13	Issue	1	Pages	60-70
	Keywords
	Abstract	Visual categorization is important to manage large collections of digital images and video, where textual meta-data is often incomplete or simply unavailable. The bag-of-words model has become the most powerful method for visual categorization of images and video. Despite its high accuracy, a severe drawback of this model is its high computational cost. As the trend to increase computational power in newer CPU and GPU architectures is to increase their level of parallelism, exploiting this parallelism becomes an important direction to handle the computational cost of the bag-of-words approach. When optimizing a system based on the bag-of-words approach, the goal is to minimize the time it takes to process batches of images. Additionally, we also consider power usage as an evaluation metric. In this paper, we analyze the bag-of-words model for visual categorization in terms of computational cost and identify two major bottlenecks: the quantization step and the classification step. We address these two bottlenecks by proposing two efficient algorithms for quantization and classification by exploiting the GPU hardware and the CUDA parallel programming model. The algorithms are designed to (1) keep categorization accuracy intact, (2) decompose the problem and (3) give the same numerical results. In the experiments on large scale datasets it is shown that, by using a parallel implementation on the Geforce GTX260 GPU, classifying unseen images is 4.8 times faster than a quad-core CPU version on the Core i7 920, while giving the exact same numerical results. In addition, we show how the algorithms can be generalized to other applications, such as text retrieval and video retrieval. Moreover, when the obtained speedup is used to process extra video frames in a video retrieval benchmark, the accuracy of visual categorization is improved by 29%.
	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			Approved	no
	Call Number	Admin @ si @ SGS2011b			Serial	1729
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	Author	Lluis Gomez; Dimosthenis Karatzas
	Title	TextProposals: a Text‐specific Selective Search Algorithm for Word Spotting in the Wild			Type	Journal Article
	Year	2017	Publication	Pattern Recognition	Abbreviated Journal	PR
	Volume	70	Issue		Pages	60-74
	Keywords
	Abstract	Motivated by the success of powerful while expensive techniques to recognize words in a holistic way (Goel et al., 2013; Almazán et al., 2014; Jaderberg et al., 2016) object proposals techniques emerge as an alternative to the traditional text detectors. In this paper we introduce a novel object proposals method that is specifically designed for text. We rely on a similarity based region grouping algorithm that generates a hierarchy of word hypotheses. Over the nodes of this hierarchy it is possible to apply a holistic word recognition method in an efficient way. Our experiments demonstrate that the presented method is superior in its ability of producing good quality word proposals when compared with class-independent algorithms. We show impressive recall rates with a few thousand proposals in different standard benchmarks, including focused or incidental text datasets, and multi-language scenarios. Moreover, the combination of our object proposals with existing whole-word recognizers (Almazán et al., 2014; Jaderberg et al., 2016) shows competitive performance in end-to-end word spotting, and, in some benchmarks, outperforms previously published results. Concretely, in the challenging ICDAR2015 Incidental Text dataset, we overcome in more than 10% F-score the best-performing method in the last ICDAR Robust Reading Competition (Karatzas, 2015). Source code of the complete end-to-end system is available at https://github.com/lluisgomez/TextProposals.
	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; 601.197; 600.121; 600.129			Approved	no
	Call Number	Admin @ si @ GoK2017			Serial	2886
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	Author	Fatemeh Noroozi; Marina Marjanovic; Angelina Njegus; Sergio Escalera; Gholamreza Anbarjafari
	Title	Audio-Visual Emotion Recognition in Video Clips			Type	Journal Article
	Year	2019	Publication	IEEE Transactions on Affective Computing	Abbreviated Journal	TAC
	Volume	10	Issue	1	Pages	60-75
	Keywords
	Abstract	This paper presents a multimodal emotion recognition system, which is based on the analysis of audio and visual cues. From the audio channel, Mel-Frequency Cepstral Coefficients, Filter Bank Energies and prosodic features are extracted. For the visual part, two strategies are considered. First, facial landmarks’ geometric relations, i.e. distances and angles, are computed. Second, we summarize each emotional video into a reduced set of key-frames, which are taught to visually discriminate between the emotions. In order to do so, a convolutional neural network is applied to key-frames summarizing videos. Finally, confidence outputs of all the classifiers from all the modalities are used to define a new feature space to be learned for final emotion label prediction, in a late fusion/stacking fashion. The experiments conducted on the SAVEE, eNTERFACE’05, and RML databases show significant performance improvements by our proposed system in comparison to current alternatives, defining the current state-of-the-art in all three databases.
	Address	1 Jan.-March 2019
	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; 602.143; 602.133			Approved	no
	Call Number	Admin @ si @ NMN2017			Serial	3011
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	Author	David Berga; Xose R. Fernandez-Vidal; Xavier Otazu; V. Leboran; Xose M. Pardo
	Title	Psychophysical evaluation of individual low-level feature influences on visual attention			Type	Journal Article
	Year	2019	Publication	Vision Research	Abbreviated Journal	VR
	Volume	154	Issue		Pages	60-79
	Keywords	Visual attention; Psychophysics; Saliency; Task; Context; Contrast; Center bias; Low-level; Synthetic; Dataset
	Abstract	In this study we provide the analysis of eye movement behavior elicited by low-level feature distinctiveness with a dataset of synthetically-generated image patterns. Design of visual stimuli was inspired by the ones used in previous psychophysical experiments, namely in free-viewing and visual searching tasks, to provide a total of 15 types of stimuli, divided according to the task and feature to be analyzed. Our interest is to analyze the influences of low-level feature contrast between a salient region and the rest of distractors, providing fixation localization characteristics and reaction time of landing inside the salient region. Eye-tracking data was collected from 34 participants during the viewing of a 230 images dataset. Results show that saliency is predominantly and distinctively influenced by: 1. feature type, 2. feature contrast, 3. temporality of fixations, 4. task difficulty and 5. center bias. This experimentation proposes a new psychophysical basis for saliency model evaluation using synthetic images.
	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	NEUROBIT; 600.128; 600.120			Approved	no
	Call Number	Admin @ si @ BFO2019a			Serial	3274
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	Author	Joan Mas; J.A. Jorge; Gemma Sanchez; Josep Llados
	Title	Describing and Parising Hand-Drawn Sketches using a Syntactic Approach			Type	Conference Article
	Year	2007	Publication	Seventh IAPR International Workshop on Graphics Recognition	Abbreviated Journal
	Volume		Issue		Pages	61–62
	Keywords
	Abstract
	Address	Curitiba (Brasil)
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor	J. Llados, W. Liu, J.M. Ogier
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	GREC
	Notes	DAG			Approved	no
	Call Number	DAG @ dag @ MJS2007			Serial	845
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	Author	Agata Lapedriza; David Masip; Jordi Vitria
	Title	Subject Recognition Using a New Approach for Feature Extraction			Type	Conference Article
	Year	2008	Publication	3rd International Conference on Computer Vision Theory and Applications	Abbreviated Journal
	Volume	2	Issue		Pages	61–66
	Keywords
	Abstract
	Address	Madeira (Portugal)
	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	VISAPP
	Notes	OR; MV			Approved	no
	Call Number	BCNPCL @ bcnpcl @ LMV2008a			Serial	980
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	Author	Marta Nuñez-Garcia; Sonja Simpraga; M.Angeles Jurado; Maite Garolera; Roser Pueyo; Laura Igual
	Title	FADR: Functional-Anatomical Discriminative Regions for rest fMRI Characterization			Type	Conference Article
	Year	2015	Publication	Machine Learning in Medical Imaging, Proceedings of 6th International Workshop, MLMI 2015, Held in Conjunction with MICCAI 2015	Abbreviated Journal
	Volume		Issue		Pages	61-68
	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	MLMI
	Notes	MILAB			Approved	no
	Call Number	Admin @ si @ NSJ2015			Serial	2674
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	Author	Dimosthenis Karatzas; Lluis Gomez; Marçal Rusiñol; Anguelos Nicolaou
	Title	The Robust Reading Competition Annotation and Evaluation Platform			Type	Conference Article
	Year	2018	Publication	13th IAPR International Workshop on Document Analysis Systems	Abbreviated Journal
	Volume		Issue		Pages	61-66
	Keywords
	Abstract	The ICDAR Robust Reading Competition (RRC), initiated in 2003 and reestablished in 2011, has become the defacto evaluation standard for the international community. Concurrent with its second incarnation in 2011, a continuous effort started to develop an online framework to facilitate the hosting and management of competitions. This short paper briefly outlines the Robust Reading Competition Annotation and Evaluation Platform, the backbone of the Robust Reading Competition, comprising a collection of tools and processes that aim to simplify the management and annotation of data, and to provide online and offline performance evaluation and analysis services.
	Address	Viena; Austria; April 2018
	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; 600.084; 600.121			Approved	no
	Call Number	KGR2018			Serial	3103
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	Author	Jorge Bernal; F. Javier Sanchez; Fernando Vilariño
	Title	Current Challenges on Polyp Detection in Colonoscopy Videos: From Region Segmentation to Region Classification. a Pattern Recognition-based Approach.ased Approach			Type	Conference Article
	Year	2011	Publication	2nd International Workshop on Medical Image Analysis and Descriptionfor Diagnosis Systems	Abbreviated Journal
	Volume		Issue		Pages	62-71
	Keywords	Medical Imaging, Colonoscopy, Pattern Recognition, Segmentation, Polyp Detection, Region Description, Machine Learning, Real-time.
	Abstract	In this paper we present our approach on real-time polyp detection in colonoscopy videos. Our method consists of three stages: Image Segmentation, Region Description and Image Classification. Taking into account the constraints of our project, we introduce our segmentation system that is based on the model of appearance of the polyp that we have defined after observing real videos from colonoscopy processes. The output of this stage will ideally be a low number of regions of which one of them should cover the whole polyp region (if there is one in the image). This regions will be described in terms of features and, as a result of a machine learning schema, classified based on the values that they have for the several features that we will use on their description. Although we are still on the early stages of the project, we present some preliminary segmentation results that indicates that we are going in a good direction.
	Address	Rome, Italy
	Corporate Author				Thesis
	Publisher	SciTePress	Place of Publication		Editor	Djemal, Khalifa
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area	800	Expedition		Conference	MIAD
	Notes	MV;SIAI			Approved	no
	Call Number	IAM @ iam @ BSV2011a			Serial	1695
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	Author	Carles Sanchez; Debora Gil; Jorge Bernal; F. Javier Sanchez; Marta Diez-Ferrer; Antoni Rosell
	Title	Navigation Path Retrieval from Videobronchoscopy using Bronchial Branches			Type	Conference Article
	Year	2016	Publication	19th International Conference on Medical Image Computing and Computer Assisted Intervention Workshops	Abbreviated Journal
	Volume	9401	Issue		Pages	62-70
	Keywords	Bronchoscopy navigation; Lumen center; Brochial branches; Navigation path; Videobronchoscopy
	Abstract	Bronchoscopy biopsy can be used to diagnose lung cancer without risking complications of other interventions like transthoracic needle aspiration. During bronchoscopy, the clinician has to navigate through the bronchial tree to the target lesion. A main drawback is the difficulty to check whether the exploration is following the correct path. The usual guidance using fluoroscopy implies repeated radiation of the clinician, while alternative systems (like electromagnetic navigation) require specific equipment that increases intervention costs. We propose to compute the navigated path using anatomical landmarks extracted from the sole analysis of videobronchoscopy images. Such landmarks allow matching the current exploration to the path previously planned on a CT to indicate clinician whether the planning is being correctly followed or not. We present a feasibility study of our landmark based CT-video matching using bronchoscopic videos simulated on a virtual bronchoscopy interactive interface.
	Address	Quebec; Canada; September 2016
	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	MICCAIW
	Notes	IAM; MV; 600.060; 600.075			Approved	no
	Call Number	Admin @ si @ SGB2016			Serial	2885
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	Author	Carola Figueroa Flores; Abel Gonzalez-Garcia; Joost Van de Weijer; Bogdan Raducanu
	Title	Saliency for fine-grained object recognition in domains with scarce training data			Type	Journal Article
	Year	2019	Publication	Pattern Recognition	Abbreviated Journal	PR
	Volume	94	Issue		Pages	62-73
	Keywords
	Abstract	This paper investigates the role of saliency to improve the classification accuracy of a Convolutional Neural Network (CNN) for the case when scarce training data is available. Our approach consists in adding a saliency branch to an existing CNN architecture which is used to modulate the standard bottom-up visual features from the original image input, acting as an attentional mechanism that guides the feature extraction process. The main aim of the proposed approach is to enable the effective training of a fine-grained recognition model with limited training samples and to improve the performance on the task, thereby alleviating the need to annotate a large dataset. The vast majority of saliency methods are evaluated on their ability to generate saliency maps, and not on their functionality in a complete vision pipeline. Our proposed pipeline allows to evaluate saliency methods for the high-level task of object recognition. We perform extensive experiments on various fine-grained datasets (Flowers, Birds, Cars, and Dogs) under different conditions and show that saliency can considerably improve the network’s performance, especially for the case of scarce training data. Furthermore, our experiments show that saliency methods that obtain improved saliency maps (as measured by traditional saliency benchmarks) also translate to saliency methods that yield improved performance gains when applied in an object recognition pipeline.
	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; 600.109; 600.141; 600.120			Approved	no
	Call Number	Admin @ si @ FGW2019			Serial	3264
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	Author	Jose Antonio Rodriguez; Gemma Sanchez; Josep Llados
	Title	Categorization of Digital Ink Elements using Spectral Features			Type	Conference Article
	Year	2007	Publication	Seventh IAPR International Workshop on Graphics Recognition	Abbreviated Journal
	Volume		Issue		Pages	63–64
	Keywords
	Abstract
	Address	Curitiba (Brazil)
	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	GREC
	Notes	DAG			Approved	no
	Call Number	DAG @ dag @ RSL2007c			Serial	888
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	Author	Agata Lapedriza; Jaume Garcia; Ernest Valveny; Robert Benavente; Miquel Ferrer; Gemma Sanchez
	Title	Una experiencia de aprenentatge basada en projectes en el ambit de la informatica			Type	Miscellaneous
	Year	2008	Publication	V Jornades d’Innovacio Docent (UAB)	Abbreviated Journal
	Volume		Issue		Pages	63
	Keywords
	Abstract
	Address	Bellaterra (Spain)
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	OR; IAM; DAG; CIC; MV			Approved	no
	Call Number	BCNPCL @ bcnpcl @ LGV2008			Serial	1030
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	Author	Marçal Rusiñol; David Aldavert; Ricardo Toledo; Josep Llados
	Title	Browsing Heterogeneous Document Collections by a Segmentation-Free Word Spotting Method			Type	Conference Article
	Year	2011	Publication	11th International Conference on Document Analysis and Recognition	Abbreviated Journal
	Volume		Issue		Pages	63-67
	Keywords
	Abstract	In this paper, we present a segmentation-free word spotting method that is able to deal with heterogeneous document image collections. We propose a patch-based framework where patches are represented by a bag-of-visual-words model powered by SIFT descriptors. A later refinement of the feature vectors is performed by applying the latent semantic indexing technique. The proposed method performs well on both handwritten and typewritten historical document images. We have also tested our method on documents written in non-Latin scripts.
	Address	Beijing, China
	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	ICDAR
	Notes	DAG;ADAS			Approved	no
	Call Number	Admin @ si @ RAT2011			Serial	1788
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