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	Author	Michal Drozdzal; Santiago Segui; Carolina Malagelada; Fernando Azpiroz; Petia Radeva
	Title	Adaptable image cuts for motility inspection using WCE			Type	Journal Article
	Year	2013	Publication	Computerized Medical Imaging and Graphics	Abbreviated Journal	CMIG
	Volume	37	Issue	1	Pages	72-80
	Keywords
	Abstract	The Wireless Capsule Endoscopy (WCE) technology allows the visualization of the whole small intestine tract. Since the capsule is freely moving, mainly by the means of peristalsis, the data acquired during the study gives a lot of information about the intestinal motility. However, due to: (1) huge amount of frames, (2) complex intestinal scene appearance and (3) intestinal dynamics that make difficult the visualization of the small intestine physiological phenomena, the analysis of the WCE data requires computer-aided systems to speed up the analysis. In this paper, we propose an efficient algorithm for building a novel representation of the WCE video data, optimal for motility analysis and inspection. The algorithm transforms the 3D video data into 2D longitudinal view by choosing the most informative, from the intestinal motility point of view, part of each frame. This step maximizes the lumen visibility in its longitudinal extension. The task of finding “the best longitudinal view” has been defined as a cost function optimization problem which global minimum is obtained by using Dynamic Programming. Validation on both synthetic data and WCE data shows that the adaptive longitudinal view is a good alternative to the traditional motility analysis done by video analysis. The proposed novel data representation a new, holistic insight into the small intestine motility, allowing to easily define and analyze motility events that are difficult to spot by analyzing WCE video. Moreover, the visual inspection of small intestine motility is 4 times faster then by means of video skimming of the WCE.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	MILAB; OR; 600.046; 605.203			Approved	no
	Call Number	Admin @ si @ DSM2012			Serial	2151
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	Author	Jorge Bernal; David Vazquez (eds)
	Title	Computer vision Trends and Challenges			Type	Book Whole
	Year	2013	Publication	Computer vision Trends and Challenges	Abbreviated Journal
	Volume		Issue		Pages
	Keywords	CVCRD; Computer Vision
	Abstract	This book contains the papers presented at the Eighth CVC Workshop on Computer Vision Trends and Challenges (CVCR&D'2013). The workshop was held at the Computer Vision Center (Universitat Autònoma de Barcelona), the October 25th, 2013. The CVC workshops provide an excellent opportunity for young researchers and project engineers to share new ideas and knowledge about the progress of their work, and also, to discuss about challenges and future perspectives. In addition, the workshop is the welcome event for new people that recently have joined the institute. The program of CVCR&D is organized in a single-track single-day workshop. It comprises several sessions dedicated to specific topics. For each session, a doctor working on the topic introduces the general research lines. The PhD students expose their specific research. A poster session will be held for open questions. Session topics cover the current research lines and development projects of the CVC: Medical Imaging, Medical Imaging, Color & Texture Analysis, Object Recognition, Image Sequence Evaluation, Advanced Driver Assistance Systems, Machine Vision, Document Analysis, Pattern Recognition and Applications. We want to thank all paper authors and Program Committee members. Their contribution shows that the CVC has a dynamic, active, and promising scientific community. We hope you all enjoy this Eighth workshop and we are looking forward to meeting you and new people next year in the Ninth CVCR&D.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor	Jorge Bernal; David Vazquez
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-84-940902-2-6	Medium
	Area		Expedition		Conference
	Notes				Approved	no
	Call Number	ADAS @ adas @ BeV2013			Serial	2339
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	Author	Bhaskar Chakraborty; Jordi Gonzalez; Xavier Roca
	Title	Large scale continuous visual event recognition using max-margin Hough transformation framework			Type	Journal Article
	Year	2013	Publication	Computer Vision and Image Understanding	Abbreviated Journal	CVIU
	Volume	117	Issue	10	Pages	1356–1368
	Keywords
	Abstract	In this paper we propose a novel method for continuous visual event recognition (CVER) on a large scale video dataset using max-margin Hough transformation framework. Due to high scalability, diverse real environmental state and wide scene variability direct application of action recognition/detection methods such as spatio-temporal interest point (STIP)-local feature based technique, on the whole dataset is practically infeasible. To address this problem, we apply a motion region extraction technique which is based on motion segmentation and region clustering to identify possible candidate “event of interest” as a preprocessing step. On these candidate regions a STIP detector is applied and local motion features are computed. For activity representation we use generalized Hough transform framework where each feature point casts a weighted vote for possible activity class centre. A max-margin frame work is applied to learn the feature codebook weight. For activity detection, peaks in the Hough voting space are taken into account and initial event hypothesis is generated using the spatio-temporal information of the participating STIPs. For event recognition a verification Support Vector Machine is used. An extensive evaluation on benchmark large scale video surveillance dataset (VIRAT) and as well on a small scale benchmark dataset (MSR) shows that the proposed method is applicable on a wide range of continuous visual event recognition applications having extremely challenging conditions.
	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	1077-3142	ISBN		Medium
	Area		Expedition		Conference
	Notes	ISE			Approved	no
	Call Number	Admin @ si @ CGR2013			Serial	2413
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	Author	Kaida Xiao; Chenyang Fu; D.Mylonas; Dimosthenis Karatzas; S. Wuerger
	Title	Unique Hue Data for Colour Appearance Models. Part ii: Chromatic Adaptation Transform			Type	Journal Article
	Year	2013	Publication	Color Research & Application	Abbreviated Journal	CRA
	Volume	38	Issue	1	Pages	22-29
	Keywords
	Abstract	Unique hue settings of 185 observers under three room-lighting conditions were used to evaluate the accuracy of full and mixed chromatic adaptation transform models of CIECAM02 in terms of unique hue reproduction. Perceptual hue shifts in CIECAM02 were evaluated for both models with no clear difference using the current Commission Internationale de l'Éclairage (CIE) recommendation for mixed chromatic adaptation ratio. Using our large dataset of unique hue data as a benchmark, an optimised parameter is proposed for chromatic adaptation under mixed illumination conditions that produces more accurate results in unique hue reproduction. © 2011 Wiley Periodicals, Inc. Col Res Appl, 2013
	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			Approved	no
	Call Number	Admin @ si @ XFM2013			Serial	1822
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	Author	David Roche; Debora Gil; Jesus Giraldo
	Title	Mechanistic analysis of the function of agonists and allosteric modulators: Reconciling two-state and operational models			Type	Journal Article
	Year	2013	Publication	British Journal of Pharmacology	Abbreviated Journal	BJP
	Volume	169	Issue	6	Pages	1189-202
	Keywords
	Abstract	Two-state and operational models of both agonism and allosterism are compared to identify and characterize common pharmacological parameters. To account for the receptor-dependent basal response, constitutive receptor activity is considered in the operational models. By arranging two-state models as the fraction of active receptors and operational models as the fractional response relative to the maximum effect of the system, a one-by-one correspondence between parameters is found. The comparative analysis allows a better understanding of complex allosteric interactions. In particular, the inclusion of constitutive receptor activity in the operational model of allosterism allows the characterization of modulators able to lower the basal response of the system; that is, allosteric modulators with negative intrinsic efficacy. Theoretical simulations and overall goodness of fit of the models to simulated data suggest that it is feasible to apply the models to experimental data and constitute one step forward in receptor theory formalism.
	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	IAM; 600.044; 605.203			Approved	no
	Call Number	IAM @ iam @ RGG2013b			Serial	2195
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	Author	Jaume Amores
	Title	Multiple Instance Classification: review, taxonomy and comparative study			Type	Journal Article
	Year	2013	Publication	Artificial Intelligence	Abbreviated Journal	AI
	Volume	201	Issue		Pages	81-105
	Keywords	Multi-instance learning; Codebook; Bag-of-Words
	Abstract	Multiple Instance Learning (MIL) has become an important topic in the pattern recognition community, and many solutions to this problemhave been proposed until now. Despite this fact, there is a lack of comparative studies that shed light into the characteristics and behavior of the different methods. In this work we provide such an analysis focused on the classification task (i.e.,leaving out other learning tasks such as regression). In order to perform our study, we implemented fourteen methods grouped into three different families. We analyze the performance of the approaches across a variety of well-known databases, and we also study their behavior in synthetic scenarios in order to highlight their characteristics. As a result of this analysis, we conclude that methods that extract global bag-level information show a clearly superior performance in general. In this sense, the analysis permits us to understand why some types of methods are more successful than others, and it permits us to establish guidelines in the design of new MIL methods.
	Address
	Corporate Author				Thesis
	Publisher	Elsevier Science Publishers Ltd. Essex, UK	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	0004-3702	ISBN		Medium
	Area		Expedition		Conference
	Notes	ADAS; 601.042; 600.057			Approved	no
	Call Number	Admin @ si @ Amo2013			Serial	2273
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	Author	Jiaolong Xu; Sebastian Ramos; Xu Hu; David Vazquez; Antonio Lopez
	Title	Multi-task Bilinear Classifiers for Visual Domain Adaptation			Type	Conference Article
	Year	2013	Publication	Advances in Neural Information Processing Systems Workshop	Abbreviated Journal
	Volume		Issue		Pages
	Keywords	Domain Adaptation; Pedestrian Detection; ADAS
	Abstract	We propose a method that aims to lessen the significant accuracy degradation that a discriminative classifier can suffer when it is trained in a specific domain (source domain) and applied in a different one (target domain). The principal reason for this degradation is the discrepancies in the distribution of the features that feed the classifier in different domains. Therefore, we propose a domain adaptation method that maps the features from the different domains into a common subspace and learns a discriminative domain-invariant classifier within it. Our algorithm combines bilinear classifiers and multi-task learning for domain adaptation. The bilinear classifier encodes the feature transformation and classification parameters by a matrix decomposition. In this way, specific feature transformations for multiple domains and a shared classifier are jointly learned in a multi-task learning framework. Focusing on domain adaptation for visual object detection, we apply this method to the state-of-the-art deformable part-based model for cross domain pedestrian detection. Experimental results show that our method significantly avoids the domain drift and improves the accuracy when compared to several baselines.
	Address	Lake Tahoe; Nevada; USA; December 2013
	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	NIPSW
	Notes	ADAS; 600.054; 600.057; 601.217;ISE			Approved	no
	Call Number	ADAS @ adas @ XRH2013			Serial	2340
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	Author	Anastasios Doulamis; Nikolaos Doulamis; Marco Bertini; Jordi Gonzalez; Thomas B. Moeslund
	Title	Analysis and Retrieval of Tracked Events and Motion in Imagery Streams			Type	Miscellaneous
	Year	2013	Publication	ACM/IEEE international workshop on Analysis and retrieval of tracked events and motion in imagery stream	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	Address	Barcelona; October 2013
	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 @ DDB2013			Serial	2372
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	Author	Debora Gil; Agnes Borras; Sergio Vera; Miguel Angel Gonzalez Ballester
	Title	A Validation Benchmark for Assessment of Medial Surface Quality for Medical Applications			Type	Conference Article
	Year	2013	Publication	9th International Conference on Computer Vision Systems	Abbreviated Journal
	Volume	7963	Issue		Pages	334-343
	Keywords	Medial Surfaces; Shape Representation; Medical Applications; Performance Evaluation
	Abstract	Confident use of medial surfaces in medical decision support systems requires evaluating their quality for detecting pathological deformations and describing anatomical volumes. Validation in the medical imaging field is a challenging task mainly due to the difficulties for getting consensual ground truth. In this paper we propose a validation benchmark for assessing medial surfaces in the context of medical applications. Our benchmark includes a home-made database of synthetic medial surfaces and volumes and specific scores for evaluating surface accuracy, its stability against volume deformations and its capabilities for accurate reconstruction of anatomical volumes.
	Address	Sant Petersburg; Russia; July 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	978-3-642-39401-0	Medium
	Area		Expedition		Conference	ICVS
	Notes	IAM; 600.044; 600.060			Approved	no
	Call Number	Admin @ si @ GBV2013			Serial	2300
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	Author	Patricia Marquez; Debora Gil; Aura Hernandez-Sabate; Daniel Kondermann
	Title	When Is A Confidence Measure Good Enough?			Type	Conference Article
	Year	2013	Publication	9th International Conference on Computer Vision Systems	Abbreviated Journal
	Volume	7963	Issue		Pages	344-353
	Keywords	Optical flow, confidence measure, performance evaluation
	Abstract	Confidence estimation has recently become a hot topic in image processing and computer vision.Yet, several definitions exist of the term “confidence” which are sometimes used interchangeably. This is a position paper, in which we aim to give an overview on existing definitions, thereby clarifying the meaning of the used terms to facilitate further research in this field. Based on these clarifications, we develop a theory to compare confidence measures with respect to their quality.
	Address	St Petersburg; Russia; July 2013
	Corporate Author				Thesis
	Publisher	Springer Link	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	978-3-642-39401-0	Medium
	Area		Expedition		Conference	ICVS
	Notes	IAM;ADAS; 600.044; 600.057; 600.060; 601.145			Approved	no
	Call Number	IAM @ iam @ MGH2013a			Serial	2218
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	Author	Andreas Møgelmose; Chris Bahnsen; Thomas B. Moeslund; Albert Clapes; Sergio Escalera
	Title	Tri-modal Person Re-identification with RGB, Depth and Thermal Features			Type	Conference Article
	Year	2013	Publication	9th IEEE Workshop on Perception beyond the visible Spectrum, Computer Vision and Pattern Recognition	Abbreviated Journal
	Volume		Issue		Pages	301-307
	Keywords
	Abstract	Person re-identification is about recognizing people who have passed by a sensor earlier. Previous work is mainly based on RGB data, but in this work we for the first time present a system where we combine RGB, depth, and thermal data for re-identification purposes. First, from each of the three modalities, we obtain some particular features: from RGB data, we model color information from different regions of the body, from depth data, we compute different soft body biometrics, and from thermal data, we extract local structural information. Then, the three information types are combined in a joined classifier. The tri-modal system is evaluated on a new RGB-D-T dataset, showing successful results in re-identification scenarios.
	Address	Portland; oregon; June 2013
	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	978-0-7695-4990-3	Medium
	Area		Expedition		Conference	CVPRW
	Notes	HUPBA;MILAB			Approved	no
	Call Number	Admin @ si @ MBM2013			Serial	2253
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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	Joan M. Nuñez; Debora Gil; Fernando Vilariño
	Title	Finger joint characterization from X-ray images for rheymatoid arthritis assessment			Type	Conference Article
	Year	2013	Publication	6th International Conference on Biomedical Electronics and Devices	Abbreviated Journal
	Volume		Issue		Pages	288-292
	Keywords	Rheumatoid Arthritis; X-Ray; Hand Joint; Sclerosis; Sharp Van der Heijde
	Abstract	In this study we propose amodular systemfor automatic rheumatoid arthritis assessment which provides a joint space width measure. A hand joint model is proposed based on the accurate analysis of a X-ray finger joint image sample set. This model shows that the sclerosis and the lower bone are the main necessary features in order to perform a proper finger joint characterization. We propose sclerosis and lower bone detection methods as well as the experimental setup necessary for its performance assessment. Our characterization is used to propose and compute a joint space width score which is shown to be related to the different degrees of arthritis. This assertion is verified by comparing our proposed score with Sharp Van der Heijde score, confirming that the lower our score is the more advanced is the patient affection.
	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	BIODEVICES
	Notes	IAM;MV; 600.057; 600.054;SIAI			Approved	no
	Call Number	IAM @ iam @ NGV2013			Serial	2196
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	Author	Francesco Ciompi; Rui Hua; Simone Balocco; Marina Alberti; Oriol Pujol; Carles Caus; J. 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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