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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	Francesco Ciompi; Rui Hua; Simone Balocco; Marina Alberti; Oriol Pujol; Carles Caus; Josepa Mauri; Petia Radeva
	Title	Learning to Detect Stent Struts in Intravascular Ultrasound			Type	Conference Article
	Year	2013	Publication	6th Iberian Conference on Pattern Recognition and Image Analysis	Abbreviated Journal
	Volume	7887	Issue		Pages	575-583
	Keywords
	Abstract	In this paper we tackle the automatic detection of struts elements (metallic braces of a stent device) in Intravascular Ultrasound (IVUS) sequences. The proposed method is based on context-aware classification of IVUS images, where we use Multi-Class Multi-Scale Stacked Sequential Learning (M2SSL). Additionally, we introduce a novel technique to reduce the amount of required contextual features. The comparison with binary and multi-class learning is also performed, using a dataset of IVUS images with struts manually annotated by an expert. The best performing configuration reaches a F-measure F = 63.97% .
	Address	Madeira; 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
	Series Volume		Series Issue		Edition
	ISSN	0302-9743	ISBN	978-3-642-38627-5	Medium
	Area		Expedition		Conference	IbPRIA
	Notes	MILAB; HuPBA; 605.203; 600.046			Approved	no
	Call Number	Admin @ si @ CHB2013			Serial	2349
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	Author	Francisco Alvaro; Francisco Cruz; Joan Andreu Sanchez; Oriol Ramos Terrades; Jose Miguel Bemedi
	Title	Page Segmentation of Structured Documents Using 2D Stochastic Context-Free Grammars			Type	Conference Article
	Year	2013	Publication	6th Iberian Conference on Pattern Recognition and Image Analysis	Abbreviated Journal
	Volume	7887	Issue		Pages	133-140
	Keywords
	Abstract	In this paper we define a bidimensional extension of Stochastic Context-Free Grammars for page segmentation of structured documents. Two sets of text classification features are used to perform an initial classification of each zone of the page. Then, the page segmentation is obtained as the most likely hypothesis according to a grammar. This approach is compared to Conditional Random Fields and results show significant improvements in several cases. Furthermore, grammars provide a detailed segmentation that allowed a semantic evaluation which also validates this model.
	Address	Madeira; 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	978-3-642-38627-5	Medium
	Area		Expedition		Conference	IbPRIA
	Notes	DAG; 605.203			Approved	no
	Call Number	Admin @ si @ ACS2013			Serial	2328
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	Author	Adriana Romero; Carlo Gatta
	Title	Do We Really Need All These Neurons?			Type	Conference Article
	Year	2013	Publication	6th Iberian Conference on Pattern Recognition and Image Analysis	Abbreviated Journal
	Volume	7887	Issue		Pages	460--467
	Keywords	Retricted Boltzmann Machine; hidden units; unsupervised learning; classification
	Abstract	Restricted Boltzmann Machines (RBMs) are generative neural networks that have received much attention recently. In particular, choosing the appropriate number of hidden units is important as it might hinder their representative power. According to the literature, RBM require numerous hidden units to approximate any distribution properly. In this paper, we present an experiment to determine whether such amount of hidden units is required in a classification context. We then propose an incremental algorithm that trains RBM reusing the previously trained parameters using a trade-off measure to determine the appropriate number of hidden units. Results on the MNIST and OCR letters databases show that using a number of hidden units, which is one order of magnitude smaller than the literature estimate, suffices to achieve similar performance. Moreover, the proposed algorithm allows to estimate the required number of hidden units without the need of training many RBM from scratch.
	Address	Madeira; 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	978-3-642-38627-5	Medium
	Area		Expedition		Conference	IbPRIA
	Notes	MILAB; 600.046			Approved	no
	Call Number	Admin @ si @ RoG2013			Serial	2311
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	Author	Antonio Clavelli; Dimosthenis Karatzas; Josep Llados; Mario Ferraro; Giuseppe Boccignone
	Title	Towards Modelling an Attention-Based Text Localization Process			Type	Conference Article
	Year	2013	Publication	6th Iberian Conference on Pattern Recognition and Image Analysis	Abbreviated Journal
	Volume	7887	Issue		Pages	296-303
	Keywords	text localization; visual attention; eye guidance
	Abstract	This note introduces a visual attention model of text localization in real-world scenes. The core of the model built upon the proto-object concept is discussed. It is shown how such dynamic mid-level representation of the scene can be derived in the framework of an action-perception loop engaging salience, text information value computation, and eye guidance mechanisms. Preliminary results that compare model generated scanpaths with those eye-tracked from human subjects are presented.
	Address	Madeira; 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	978-3-642-38627-5	Medium
	Area		Expedition		Conference	IbPRIA
	Notes	DAG			Approved	no
	Call Number	Admin @ si @ CKL2013			Serial	2291
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	Author	Nuria Cirera; Alicia Fornes; Volkmar Frinken; Josep Llados
	Title	Hybrid grammar language model for handwritten historical documents recognition			Type	Conference Article
	Year	2013	Publication	6th Iberian Conference on Pattern Recognition and Image Analysis	Abbreviated Journal
	Volume	7887	Issue		Pages	117-124
	Keywords
	Abstract	In this paper we present a hybrid language model for the recognition of handwritten historical documents with a structured syntactical layout. Using a hidden Markov model-based recognition framework, a word-based grammar with a closed dictionary is enhanced by a character sequence recognition method. This allows to recognize out-of-dictionary words in controlled parts of the recognition, while keeping a closed vocabulary restriction for other parts. While the current status is work in progress, we can report an improvement in terms of character error rate.
	Address	Madeira; 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	978-3-642-38627-5	Medium
	Area		Expedition		Conference	IbPRIA
	Notes	DAG; 602.006; 600.045; 600.061			Approved	no
	Call Number	Admin @ si @ CFF2013			Serial	2292
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	Author	D.Sanchez; J.C.Ortega; Miguel Angel Bautista
	Title	Human Body Segmentation with Multi-limb Error-Correcting Output Codes Detection and Graph Cuts Optimization			Type	Conference Article
	Year	2013	Publication	6th Iberian Conference on Pattern Recognition and Image Analysis	Abbreviated Journal
	Volume	7887	Issue		Pages	50-58
	Keywords	Human Body Segmentation; Error-Correcting Output Codes; Cascade of Classifiers; Graph Cuts
	Abstract	Human body segmentation is a hard task because of the high variability in appearance produced by changes in the point of view, lighting conditions, and number of articulations of the human body. In this paper, we propose a two-stage approach for the segmentation of the human body. In a first step, a set of human limbs are described, normalized to be rotation invariant, and trained using cascade of classifiers to be split in a tree structure way. Once the tree structure is trained, it is included in a ternary Error-Correcting Output Codes (ECOC) framework. This first classification step is applied in a windowing way on a new test image, defining a body-like probability map, which is used as an initialization of a GMM color modelling and binary Graph Cuts optimization procedure. The proposed methodology is tested in a novel limb-labelled data set. Results show performance improvements of the novel approach in comparison to classical cascade of classifiers and human detector-based Graph Cuts segmentation approaches.
	Address	Madeira; 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	978-3-642-38627-5	Medium
	Area		Expedition		Conference	IbPRIA
	Notes	HUPBA			Approved	no
	Call Number	SOB2013			Serial	2250
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	Author	Mohammad Ali Bagheri; Qigang Gao; Sergio Escalera
	Title	Logo recognition Based on the Dempster-Shafer Fusion of Multiple Classifiers			Type	Conference Article
	Year	2013	Publication	26th Canadian Conference on Artificial Intelligence	Abbreviated Journal
	Volume	7884	Issue		Pages	1-12
	Keywords	Logo recognition; ensemble classification; Dempster-Shafer fusion; Zernike moments; generic Fourier descriptor; shape signature
	Abstract	Best paper award The performance of different feature extraction and shape description methods in trademark image recognition systems have been studied by several researchers. However, the potential improvement in classification through feature fusion by ensemble-based methods has remained unattended. In this work, we evaluate the performance of an ensemble of three classifiers, each trained on different feature sets. Three promising shape description techniques, including Zernike moments, generic Fourier descriptors, and shape signature are used to extract informative features from logo images, and each set of features is fed into an individual classifier. In order to reduce recognition error, a powerful combination strategy based on the Dempster-Shafer theory is utilized to fuse the three classifiers trained on different sources of information. This combination strategy can effectively make use of diversity of base learners generated with different set of features. The recognition results of the individual classifiers are compared with those obtained from fusing the classifiers’ output, showing significant performance improvements of the proposed methodology.
	Address	Canada; May 2013
	Corporate Author				Thesis
	Publisher	Springer Berlin Heidelberg	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	0302-9743	ISBN	978-3-642-38456-1	Medium
	Area		Expedition		Conference	AI
	Notes	HuPBA;MILAB			Approved	no
	Call Number	Admin @ si @ BGE2013b			Serial	2249
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	Author	Andreas Fischer; Ching Y. Suen; Volkmar Frinken; Kaspar Riesen; Horst Bunke
	Title	A Fast Matching Algorithm for Graph-Based Handwriting Recognition			Type	Conference Article
	Year	2013	Publication	9th IAPR – TC15 Workshop on Graph-based Representation in Pattern Recognition	Abbreviated Journal
	Volume	7877	Issue		Pages	194-203
	Keywords
	Abstract	The recognition of unconstrained handwriting images is usually based on vectorial representation and statistical classification. Despite their high representational power, graphs are rarely used in this field due to a lack of efficient graph-based recognition methods. Recently, graph similarity features have been proposed to bridge the gap between structural representation and statistical classification by means of vector space embedding. This approach has shown a high performance in terms of accuracy but had shortcomings in terms of computational speed. The time complexity of the Hungarian algorithm that is used to approximate the edit distance between two handwriting graphs is demanding for a real-world scenario. In this paper, we propose a faster graph matching algorithm which is derived from the Hausdorff distance. On the historical Parzival database it is demonstrated that the proposed method achieves a speedup factor of 12.9 without significant loss in recognition accuracy.
	Address	Vienna; Austria; May 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	978-3-642-38220-8	Medium
	Area		Expedition		Conference	GBR
	Notes	DAG; 600.045; 605.203			Approved	no
	Call Number	Admin @ si @ FSF2013			Serial	2294
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	Author	Miguel Angel Bautista; Antonio Hernandez; Victor Ponce; Xavier Perez Sala; Xavier Baro; Oriol Pujol; Cecilio Angulo; Sergio Escalera
	Title	Probability-based Dynamic TimeWarping for Gesture Recognition on RGB-D data			Type	Conference Article
	Year	2012	Publication	21st International Conference on Pattern Recognition International Workshop on Depth Image Analysis	Abbreviated Journal
	Volume	7854	Issue		Pages	126-135
	Keywords
	Abstract	Dynamic Time Warping (DTW) is commonly used in gesture recognition tasks in order to tackle the temporal length variability of gestures. In the DTW framework, a set of gesture patterns are compared one by one to a maybe infinite test sequence, and a query gesture category is recognized if a warping cost below a certain threshold is found within the test sequence. Nevertheless, either taking one single sample per gesture category or a set of isolated samples may not encode the variability of such gesture category. In this paper, a probability-based DTW for gesture recognition is proposed. Different samples of the same gesture pattern obtained from RGB-Depth data are used to build a Gaussian-based probabilistic model of the gesture. Finally, the cost of DTW has been adapted accordingly to the new model. The proposed approach is tested in a challenging scenario, showing better performance of the probability-based DTW in comparison to state-of-the-art approaches for gesture recognition on RGB-D data.
	Address
	Corporate Author				Thesis
	Publisher	Springer Berlin Heidelberg	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	0302-9743	ISBN	978-3-642-40302-6	Medium
	Area		Expedition		Conference	WDIA
	Notes	MILAB; OR;HuPBA;MV			Approved	no
	Call Number	Admin @ si @ BHP2012			Serial	2120
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	Author	Miguel Reyes; Albert Clapes; Luis Felipe Mejia; Jose Ramirez; Juan R Revilla; Sergio Escalera
	Title	Posture Analysis and Range of Movement Estimation using Depth Maps			Type	Conference Article
	Year	2012	Publication	21st International Conference on Pattern Recognition International Workshop on Depth Image Analysis	Abbreviated Journal
	Volume	7854	Issue		Pages	97-105
	Keywords
	Abstract	World Health Organization estimates that 80% of the world population is affected of back pain during his life. Current practices to analyze back problems are expensive, subjective, and invasive. In this work, we propose a novel tool for posture and range of movement estimation based on the analysis of 3D information from depth maps. Given a set of keypoints defined by the user, RGB and depth data are aligned, depth surface is reconstructed, keypoints are matching using a novel point-to-point fitting procedure, and accurate measurements about posture, spinal curvature, and range of movement are computed. The system shows high precision and reliable measurements, being useful for posture reeducation purposes to prevent musculoskeletal disorders, such as back pain, as well as tracking the posture evolution of patients in rehabilitation treatments.
	Address
	Corporate Author				Thesis
	Publisher	Springer Berlin Heidelberg	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	0302-9743	ISBN	978-3-642-40302-6	Medium
	Area		Expedition		Conference	WDIA
	Notes	HuPBA;MILAB			Approved	no
	Call Number	Admin @ si @ RCM2012			Serial	2121
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	Author	Joost Van de Weijer; Fahad Shahbaz Khan
	Title	Fusing Color and Shape for Bag-of-Words Based Object Recognition			Type	Conference Article
	Year	2013	Publication	4th Computational Color Imaging Workshop	Abbreviated Journal
	Volume	7786	Issue		Pages	25-34
	Keywords	Object Recognition; color features; bag-of-words; image classification
	Abstract	In this article we provide an analysis of existing methods for the incorporation of color in bag-of-words based image representations. We propose a list of desired properties on which bases fusing methods can be compared. We discuss existing methods and indicate shortcomings of the two well-known fusing methods, namely early and late fusion. Several recent works have addressed these shortcomings by exploiting top-down information in the bag-of-words pipeline: color attention which is motivated from human vision, and Portmanteau vocabularies which are based on information theoretic compression of product vocabularies. We point out several remaining challenges in cue fusion and provide directions for future research.
	Address	Chiba; Japan; March 2013
	Corporate Author				Thesis
	Publisher	Springer Berlin Heidelberg	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	0302-9743	ISBN	978-3-642-36699-4	Medium
	Area		Expedition		Conference	CCIW
	Notes	CIC; 600.048			Approved	no
	Call Number	Admin @ si @ WeK2013			Serial	2283
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	Author	Ferran Poveda; Debora Gil;Enric Marti
	Title	Multi-resolution DT-MRI cardiac tractography			Type	Conference Article
	Year	2012	Publication	Statistical Atlases And Computational Models Of The Heart: Imaging and Modelling Challenges	Abbreviated Journal
	Volume	7746	Issue		Pages	270-277
	Keywords
	Abstract	Even using objective measures from DT-MRI no consensus about myocardial architecture has been achieved so far. Streamlining provides good reconstructions at low level of detail, but falls short to give global abstract interpretations. In this paper, we present a multi-resolution methodology that is able to produce simplified representations of cardiac architecture. Our approach produces a reduced set of tracts that are representative of the main geometric features of myocardial anatomical structure. Experiments show that fiber geometry is preserved along reductions, which validates the simplified model for interpretation of cardiac architecture.
	Address	Nice, France
	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	978-3-642-36960-5	Medium
	Area		Expedition		Conference	STACOM
	Notes	IAM			Approved	no
	Call Number	IAM @ iam @ PGM2012			Serial	1986
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	Author	Debora Gil;Agnes Borras;Ruth Aris;Mariano Vazquez;Pierre Lafortune; Guillame Houzeaux
	Title	What a difference in biomechanics cardiac fiber makes			Type	Conference Article
	Year	2012	Publication	Statistical Atlases And Computational Models Of The Heart: Imaging and Modelling Challenges	Abbreviated Journal
	Volume	7746	Issue		Pages	253-260
	Keywords
	Abstract	Computational simulations of the heart are a powerful tool for a comprehensive understanding of cardiac function and its intrinsic relationship with its muscular architecture. Cardiac biomechanical models require a vector field representing the orientation of cardiac fibers. A wrong orientation of the fibers can lead to a non-realistic simulation of the heart functionality. In this paper we explore the impact of the fiber information on the simulated biomechanics of cardiac muscular anatomy. We have used the John Hopkins database to perform a biomechanical simulation using both a synthetic benchmark fiber distribution and the data obtained experimentally from DTI. Results illustrate how differences in fiber orientation affect heart deformation along cardiac cycle.
	Address	Nice, France
	Corporate Author				Thesis
	Publisher	Springer Berlin Heidelberg	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	0302-9743	ISBN	978-3-642-36960-5	Medium
	Area		Expedition		Conference	STACOM
	Notes	IAM			Approved	no
	Call Number	IAM @ iam @ GBA2012			Serial	1987
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	Author	Simeon Petkov; Adriana Romero; Xavier Carrillo; Petia Radeva; Carlo Gatta
	Title	Robust and accurate diaphragm border detection in cardiac X-Ray angiographies			Type	Conference Article
	Year	2012	Publication	Statistical Atlases And Computational Models Of The Heart: Imaging and Modelling Challenges	Abbreviated Journal
	Volume	7746	Issue		Pages	225-234
	Keywords
	Abstract	Workshop STACOM, dins del MICCAI X-ray angiography is the most common imaging modality employed in the diagnosis of coronary diseases prior to or during a catheter-based intervention. The analysis of the patient X-Ray sequence can provide useful information about the degree of arterial stenosis, the myocardial perfusion and other clinical parameters. If the sequence has been acquired to evaluate the perfusion grade, the opacity due to the diaphragm could potentially hinder any kind of visual inspection and make more difficult a computer aided measurements. In this paper we propose an accurate and robust method to automatically identify the diaphragm border in each frame. Quantitative evaluation on a set of 11 sequences shows that the proposed algorithm outperforms previous methods.
	Address	Nice, France
	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	0302-9743	ISBN	978-3-642-36960-5	Medium
	Area		Expedition		Conference	STACOM
	Notes	MILAB			Approved	no
	Call Number	Admin @ si @ PRC2012			Serial	2028
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