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	Author	Joan M. Nuñez; Jorge Bernal; F. Javier Sanchez; Fernando Vilariño
	Title	Blood Vessel Characterization in Colonoscopy Images to Improve Polyp Localization			Type	Conference Article
	Year	2013	Publication	Proceedings of the International Conference on Computer Vision Theory and Applications	Abbreviated Journal
	Volume	1	Issue		Pages	162-171
	Keywords	Colonoscopy; Blood vessel; Linear features; Valley detection
	Abstract	This paper presents an approach to mitigate the contribution of blood vessels to the energy image used at different tasks of automatic colonoscopy image analysis. This goal is achieved by introducing a characterization of endoluminal scene objects which allows us to differentiate between the trace of 2-dimensional visual objects,such as vessels, and shades from 3-dimensional visual objects, such as folds. The proposed characterization is based on the influence that the object shape has in the resulting visual feature, and it leads to the development of a blood vessel attenuation algorithm. A database consisting of manually labelled masks was built in order to test the performance of our method, which shows an encouraging success in blood vessel mitigation while keeping other structures intact. Moreover, by extending our method to the only available polyp localization algorithm tested on a public database, blood vessel mitigation proved to have a positive influence on the overall performance.
	Address	Barcelona; February 2013
	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		Medium
	Area	800	Expedition		Conference	VISIGRAPP
	Notes	MV; 600.054; 600.057;SIAI			Approved	no
	Call Number	IAM @ iam @ NBS2013			Serial	2198
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	Author	Iban Berganzo-Besga; Hector A. Orengo; Felipe Lumbreras; Paloma Aliende; Monica N. Ramsey
	Title	Automated detection and classification of multi-cell Phytoliths using Deep Learning-Based Algorithms			Type	Journal Article
	Year	2022	Publication	Journal of Archaeological Science	Abbreviated Journal	JArchSci
	Volume	148	Issue		Pages	105654
	Keywords
	Abstract	This paper presents an algorithm for automated detection and classification of multi-cell phytoliths, one of the major components of many archaeological and paleoenvironmental deposits. This identification, based on phytolith wave pattern, is made using a pretrained VGG19 deep learning model. This approach has been tested in three key phytolith genera for the study of agricultural origins in Near East archaeology: Avena, Hordeum and Triticum. Also, this classification has been validated at species-level using Triticum boeoticum and dicoccoides images. Due to the diversity of microscopes, cameras and chemical treatments that can influence images of phytolith slides, three types of data augmentation techniques have been implemented: rotation of the images at 45-degree angles, random colour and brightness jittering, and random blur/sharpen. The implemented workflow has resulted in an overall accuracy of 93.68% for phytolith genera, improving previous attempts. The algorithm has also demonstrated its potential to automatize the classification of phytoliths species with an overall accuracy of 100%. The open code and platforms employed to develop the algorithm assure the method's accessibility, reproducibility and reusability.
	Address	December 2022
	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	MSIAU; MACO; 600.167			Approved	no
	Call Number	Admin @ si @ BOL2022			Serial	3753
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	Author	Gioacchino Vino; Angel Sappa
	Title	Revisiting Harris Corner Detector Algorithm: a Gradual Thresholding Approach			Type	Conference Article
	Year	2013	Publication	10th International Conference on Image Analysis and Recognition	Abbreviated Journal
	Volume	7950	Issue		Pages	354-363
	Keywords
	Abstract	This paper presents an adaptive thresholding approach intended to increase the number of detected corners, while reducing the amount of those ones corresponding to noisy data. The proposed approach works by using the classical Harris corner detector algorithm and overcome the difficulty in finding a general threshold that work well for all the images in a given data set by proposing a novel adaptive thresholding scheme. Initially, two thresholds are used to discern between strong corners and flat regions. Then, a region based criteria is used to discriminate between weak corners and noisy points in the midway interval. Experimental results show that the proposed approach has a better capability to reject false corners and, at the same time, to detect weak ones. Comparisons with the state of the art are provided showing the validity of the proposed approach.
	Address	Póvoa de Varzim; Portugal; June 2013
	Corporate Author				Thesis
	Publisher	Springer Berlin Heidelberg	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN	0302-9743	ISBN	978-3-642-39093-7	Medium
	Area		Expedition		Conference	ICIAR
	Notes	ADAS; 600.055			Approved	no
	Call Number	Admin @ si @ ViS2013			Serial	2562
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	Author	Carme Julia; Angel Sappa; Felipe Lumbreras; Joan Serrat; Antonio Lopez
	Title	An Adapted Alternation Approach for Recommender Systems			Type	Conference Article
	Year	2008	Publication	IEEE International Conference on e–Business Engineering,	Abbreviated Journal
	Volume		Issue		Pages	128–135
	Keywords
	Abstract	This paper presents an adaptation of the alternation technique to tackle the prediction task in recommender systems. These systems are widely considered in electronic commerce to help customers to find products they will probably like or dislike. As the SVD-based approaches, the proposed adapted alternation technique uses all the information stored in the system to find the predictions. The main advantage of this technique with respect to the SVD-based ones is that it can deal with missing data. Furthermore, it has a smaller computational cost. Experimental results with public data sets are provided in order to show the viability of the proposed adapted alternation approach.
	Address	Xi’an (Xina)
	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			Approved	no
	Call Number	ADAS @ adas @ JSL2008e			Serial	1044
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	Author	Arnau Ramisa; Adriana Tapus; David Aldavert; Ricardo Toledo; Ramon Lopez de Mantaras
	Title	Robust Vision-Based Localization using Combinations of Local Feature Regions Detectors			Type	Journal Article
	Year	2009	Publication	Autonomous Robots	Abbreviated Journal	AR
	Volume	27	Issue	4	Pages	373-385
	Keywords
	Abstract	This paper presents a vision-based approach for mobile robot localization. The model of the environment is topological. The new approach characterizes a place using a signature. This signature consists of a constellation of descriptors computed over different types of local affine covariant regions extracted from an omnidirectional image acquired rotating a standard camera with a pan-tilt unit. This type of representation permits a reliable and distinctive environment modelling. Our objectives were to validate the proposed method in indoor environments and, also, to find out if the combination of complementary local feature region detectors improves the localization versus using a single region detector. Our experimental results show that if false matches are effectively rejected, the combination of different covariant affine region detectors increases notably the performance of the approach by combining the different strengths of the individual detectors. In order to reduce the localization time, two strategies are evaluated: re-ranking the map nodes using a global similarity measure and using standard perspective view field of 45°. In order to systematically test topological localization methods, another contribution proposed in this work is a novel method to see the degradation in localization performance as the robot moves away from the point where the original signature was acquired. This allows to know the robustness of the proposed signature. In order for this to be effective, it must be done in several, variated, environments that test all the possible situations in which the robot may have to perform localization.
	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	0929-5593	ISBN		Medium
	Area		Expedition		Conference
	Notes	ADAS			Approved	no
	Call Number	Admin @ si @ RTA2009			Serial	1245
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	Author	Rafael E. Rivadeneira; Angel Sappa; Boris X. Vintimilla; Riad I. Hammoud
	Title	A Novel Domain Transfer-Based Approach for Unsupervised Thermal Image Super-Resolution			Type	Journal Article
	Year	2022	Publication	Sensors	Abbreviated Journal	SENS
	Volume	22	Issue	6	Pages	2254
	Keywords	Thermal image super-resolution; unsupervised super-resolution; thermal images; attention module; semiregistered thermal images
	Abstract	This paper presents a transfer domain strategy to tackle the limitations of low-resolution thermal sensors and generate higher-resolution images of reasonable quality. The proposed technique employs a CycleGAN architecture and uses a ResNet as an encoder in the generator along with an attention module and a novel loss function. The network is trained on a multi-resolution thermal image dataset acquired with three different thermal sensors. Results report better performance benchmarking results on the 2nd CVPR-PBVS-2021 thermal image super-resolution challenge than state-of-the-art methods. The code of this work is available online.
	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	MSIAU;			Approved	no
	Call Number	Admin @ si @ RSV2022b			Serial	3688
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	Author	Josep Llados; Jaime Lopez-Krahe; Enric Marti
	Title	Hand drawn document understanding using the straight line Hough transform and graph matching			Type	Conference Article
	Year	1996	Publication	Proceedings of the 13th International Pattern Recognition Conference (ICPR’96)	Abbreviated Journal
	Volume	2	Issue		Pages	497-501
	Keywords
	Abstract	This paper presents a system to understand hand drawn architectural drawings in a CAD environment. The procedure is to identify in a floor plan the building elements, stored in a library of patterns, and their spatial relationships. The vectorized input document and the patterns to recognize are represented by attributed graphs. To recognize the patterns as such, we apply a structural approach based on subgraph isomorphism techniques. In spite of their value, graph matching techniques do not recognize adequately those building elements characterized by hatching patterns, i.e. walls. Here we focus on the recognition of hatching patterns and develop a straight line Hough transform based method in order to detect the regions filled in with parallel straight fines. This allows not only to recognize filling patterns, but it actually reduces the computational load associated with the subgraph isomorphism computation. The result is that the document can be redrawn by editing all the patterns recognized
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication	Vienna , Austria	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;IAM;			Approved	no
	Call Number	IAM @ iam @ LLM1996			Serial	1579
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	Author	Joan Mas; Alicia Fornes; Josep Llados
	Title	An Interactive Transcription System of Census Records using Word-Spotting based Information Transfer			Type	Conference Article
	Year	2016	Publication	12th IAPR Workshop on Document Analysis Systems	Abbreviated Journal
	Volume		Issue		Pages	54-59
	Keywords
	Abstract	This paper presents a system to assist in the transcription of historical handwritten census records in a crowdsourcing platform. Census records have a tabular structured layout. They consist in a sequence of rows with information of homes ordered by street address. For each household snippet in the page, the list of family members is reported. The censuses are recorded in intervals of a few years and the information of individuals in each household is quite stable from a point in time to the next one. This redundancy is used to assist the transcriber, so the redundant information is transferred from the census already transcribed to the next one. Household records are aligned from one year to the next one using the knowledge of the ordering by street address. Given an already transcribed census, a query by string word spotting is applied. Thus, names from the census in time t are used as queries in the corresponding home record in time t+1. Since the search is constrained, the obtained precision-recall values are very high, with an important reduction in the transcription time. The proposed system has been tested in a real citizen-science experience where non expert users transcribe the census data of their home town.
	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; 603.053; 602.006; 600.061; 600.077; 600.097			Approved	no
	Call Number	Admin @ si @ MFL2016			Serial	2751
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	Author	Juan Ramon Terven Salinas; Joaquin Salas; Bogdan Raducanu
	Title	Robust Head Gestures Recognition for Assistive Technology			Type	Book Chapter
	Year	2014	Publication	Pattern Recognition	Abbreviated Journal
	Volume	8495	Issue		Pages	152-161
	Keywords
	Abstract	This paper presents a system capable of recognizing six head gestures: nodding, shaking, turning right, turning left, looking up, and looking down. The main difference of our system compared to other methods is that the Hidden Markov Models presented in this paper, are fully connected and consider all possible states in any given order, providing the following advantages to the system: (1) allows unconstrained movement of the head and (2) it can be easily integrated into a wearable device (e.g. glasses, neck-hung devices), in which case it can robustly recognize gestures in the presence of ego-motion. Experimental results show that this approach outperforms common methods that use restricted HMMs for each gesture.
	Address
	Corporate Author				Thesis
	Publisher	Springer International Publishing	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN	0302-9743	ISBN	978-3-319-07490-0	Medium
	Area		Expedition		Conference
	Notes	OR;MV			Approved	no
	Call Number	Admin @ si @ TSR2014b			Serial	2505
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	Author	Lluis Pere de las Heras; Gemma Sanchez
	Title	And-Or Graph Grammar for Architectural Floorplan Representation, Learning and Recognition. A Semantic, Structural and Hierarchical Model			Type	Conference Article
	Year	2011	Publication	5th Iberian Conference on Pattern Recognition and Image Analysis	Abbreviated Journal
	Volume	6669	Issue		Pages	17-24
	Keywords
	Abstract	This paper presents a syntactic model for architectural floor plan interpretation. A stochastic image grammar over an And-Or graph is inferred to represent the hierarchical, structural and semantic relations between elements of all possible floor plans. This grammar is augmented with three different probabilistic models, learnt from a training set, to account the frequency of that relations. Then, a Bottom-Up/Top-Down parser with a pruning strategy has been used for floor plan recognition. For a given input, the parser generates the most probable parse graph for that document. This graph not only contains the structural and semantic relations of its elements, but also its hierarchical composition, that allows to interpret the floor plan at different levels of abstraction.
	Address	Las Palmas de Gran Canaria. 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	978-3-642-21256-7	Medium
	Area		Expedition		Conference	IbPRIA
	Notes	DAG			Approved	no
	Call Number	Admin @ si @ HeS2011			Serial	1736
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	Author	Joan Mas; Josep Llados; Gemma Sanchez; J.A. Jorge
	Title	A syntactic approach based on distortion-tolerant Adjacency Grammars and a spatial-directed parser to interpret sketched diagrams			Type	Journal Article
	Year	2010	Publication	Pattern Recognition	Abbreviated Journal	PR
	Volume	43	Issue	12	Pages	4148–4164
	Keywords	Syntactic Pattern Recognition; Symbol recognition; Diagram understanding; Sketched diagrams; Adjacency Grammars; Incremental parsing; Spatial directed parsing
	Abstract	This paper presents a syntactic approach based on Adjacency Grammars (AG) for sketch diagram modeling and understanding. Diagrams are a combination of graphical symbols arranged according to a set of spatial rules defined by a visual language. AG describe visual shapes by productions defined in terms of terminal and non-terminal symbols (graphical primitives and subshapes), and a set functions describing the spatial arrangements between symbols. Our approach to sketch diagram understanding provides three main contributions. First, since AG are linear grammars, there is a need to define shapes and relations inherently bidimensional using a sequential formalism. Second, our parsing approach uses an indexing structure based on a spatial tessellation. This serves to reduce the search space when finding candidates to produce a valid reduction. This allows order-free parsing of 2D visual sentences while keeping combinatorial explosion in check. Third, working with sketches requires a distortion model to cope with the natural variations of hand drawn strokes. To this end we extended the basic grammar with a distortion measure modeled on the allowable variation on spatial constraints associated with grammar productions. Finally, the paper reports on an experimental framework an interactive system for sketch analysis. User tests performed on two real scenarios show that our approach is usable in interactive settings.
	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	DAG			Approved	no
	Call Number	DAG @ dag @ MLS2010			Serial	1336
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	Author	Marçal Rusiñol; Agnes Borras; Josep Llados
	Title	Relational Indexing of Vectorial Primitives for Symbol Spotting in Line-Drawing Images			Type	Journal Article
	Year	2010	Publication	Pattern Recognition Letters	Abbreviated Journal	PRL
	Volume	31	Issue	3	Pages	188–201
	Keywords	Document image analysis and recognition, Graphics recognition, Symbol spotting ,Vectorial representations, Line-drawings
	Abstract	This paper presents a symbol spotting approach for indexing by content a database of line-drawing images. As line-drawings are digital-born documents designed by vectorial softwares, instead of using a pixel-based approach, we present a spotting method based on vector primitives. Graphical symbols are represented by a set of vectorial primitives which are described by an off-the-shelf shape descriptor. A relational indexing strategy aims to retrieve symbol locations into the target documents by using a combined numerical-relational description of 2D structures. The zones which are likely to contain the queried symbol are validated by a Hough-like voting scheme. In addition, a performance evaluation framework for symbol spotting in graphical documents is proposed. The presented methodology has been evaluated with a benchmarking set of architectural documents achieving good performance results.
	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	DAG			Approved	no
	Call Number	DAG @ dag @ RBL2010			Serial	1177
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	Author	Katerine Diaz; Jesus Martinez del Rincon; Aura Hernandez-Sabate; Marçal Rusiñol; Francesc J. Ferri
	Title	Fast Kernel Generalized Discriminative Common Vectors for Feature Extraction			Type	Journal Article
	Year	2018	Publication	Journal of Mathematical Imaging and Vision	Abbreviated Journal	JMIV
	Volume	60	Issue	4	Pages	512-524
	Keywords
	Abstract	This paper presents a supervised subspace learning method called Kernel Generalized Discriminative Common Vectors (KGDCV), as a novel extension of the known Discriminative Common Vectors method with Kernels. Our method combines the advantages of kernel methods to model complex data and solve nonlinear problems with moderate computational complexity, with the better generalization properties of generalized approaches for large dimensional data. These attractive combination makes KGDCV specially suited for feature extraction and classification in computer vision, image processing and pattern recognition applications. Two different approaches to this generalization are proposed, a first one based on the kernel trick (KT) and a second one based on the nonlinear projection trick (NPT) for even higher efficiency. Both methodologies have been validated on four different image datasets containing faces, objects and handwritten digits, and compared against well known non-linear state-of-art methods. Results show better discriminant properties than other generalized approaches both linear or kernel. In addition, the KGDCV-NPT approach presents a considerable computational gain, without compromising the accuracy of the model.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	DAG; ADAS; 600.086; 600.130; 600.121; 600.118; 600.129			Approved	no
	Call Number	Admin @ si @ DMH2018a			Serial	3062
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	Author	Dimosthenis Karatzas; Sergi Robles; Lluis Gomez
	Title	An on-line platform for ground truthing and performance evaluation of text extraction systems			Type	Conference Article
	Year	2014	Publication	11th IAPR International Workshop on Document Analysis and Systems	Abbreviated Journal
	Volume		Issue		Pages	242 - 246
	Keywords
	Abstract	This paper presents a set of on-line software tools for creating ground truth and calculating performance evaluation metrics for text extraction tasks such as localization, segmentation and recognition. The platform supports the definition of comprehensive ground truth information at different text representation levels while it offers centralised management and quality control of the ground truthing effort. It implements a range of state of the art performance evaluation algorithms and offers functionality for the definition of evaluation scenarios, on-line calculation of various performance metrics and visualisation of the results. The presented platform, which comprises the backbone of the ICDAR 2011 (challenge 1) and 2013 (challenges 1 and 2) Robust Reading competitions, is now made available for public use.
	Address	Tours; Francia; April 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	978-1-4799-3243-6	Medium
	Area		Expedition		Conference	DAS
	Notes	DAG; 600.056; 600.077			Approved	no
	Call Number	Admin @ si @ KRG2014			Serial	2491
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	Author	Naveen Onkarappa; Angel Sappa
	Title	On-Board Monocular Vision System Pose Estimation through a Dense Optical Flow			Type	Conference Article
	Year	2010	Publication	7th International Conference on Image Analysis and Recognition	Abbreviated Journal
	Volume	6111	Issue		Pages	230-239
	Keywords
	Abstract	This paper presents a robust technique for estimating on-board monocular vision system pose. The proposed approach is based on a dense optical flow that is robust against shadows, reflections and illumination changes. A RANSAC based scheme is used to cope with the outliers in the optical flow. The proposed technique is intended to be used in driver assistance systems for applications such as obstacle or pedestrian detection. Experimental results on different scenarios, both from synthetic and real sequences, shows usefulness of the proposed approach.
	Address	Povoa de Varzim (Portugal)
	Corporate Author				Thesis
	Publisher	Springer Berlin Heidelberg	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN	0302-9743	ISBN	978-3-642-13771-6	Medium
	Area		Expedition		Conference	ICIAR
	Notes	ADAS			Approved	no
	Call Number	ADAS @ adas @ OnS2010			Serial	1342
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