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	Author	Ferran Poveda; Debora Gil ;Albert Andaluz ;Enric Marti
	Title	Multiscale Tractography for Representing Heart Muscular Architecture			Type	Conference Article
	Year	2011	Publication	In MICCAI 2011 Workshop on Computational Diffusion MRI	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract	Deep understanding of myocardial structure of the heart would unravel crucial knowledge for clinical and medical procedures. Although the muscular architecture of the heart has been debated by countless researchers, the controversy is still alive. Diﬀusion Tensor MRI, DT-MRI, is a unique imaging technique for computational validation of the muscular structure of the heart. By the complex arrangement of myocites, existing techniques can not provide comprehensive descriptions of the global muscular architecture. In this paper we introduce a multiresolution reconstruction technique based on DT-MRI streamlining for simpliﬁed global myocardial model generation. Our reconstructions can restore the most complex myocardial structures and indicate a global helical organization
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language	English	Summary Language	english	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	CDRMI
	Notes	IAM			Approved	no
	Call Number	IAM @ iam @ PGA2011			Serial	1681
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	Author	Patricia Marquez; Debora Gil; Aura Hernandez-Sabate
	Title	A Confidence Measure for Assessing Optical Flow Accuracy in the Absence of Ground Truth			Type	Conference Article
	Year	2011	Publication	IEEE International Conference on Computer Vision – Workshops	Abbreviated Journal
	Volume		Issue		Pages	2042-2049
	Keywords	IEEE International Conference on Computer Vision – Workshops
	Abstract	Optical flow is a valuable tool for motion analysis in autonomous navigation systems. A reliable application requires determining the accuracy of the computed optical flow. This is a main challenge given the absence of ground truth in real world sequences. This paper introduces a measure of optical flow accuracy for Lucas-Kanade based flows in terms of the numerical stability of the data-term. We call this measure optical flow condition number. A statistical analysis over ground-truth data show a good statistical correlation between the condition number and optical flow error. Experiments on driving sequences illustrate its potential for autonomous navigation systems.
	Address
	Corporate Author				Thesis
	Publisher	IEEE	Place of Publication	Barcelona (Spain)	Editor
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	ICCVW
	Notes	IAM; ADAS			Approved	no
	Call Number	IAM @ iam @ MGH2011			Serial	1682
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	Author	David Vazquez; Antonio Lopez; Daniel Ponsa; Javier Marin
	Title	Virtual Worlds and Active Learning for Human Detection			Type	Conference Article
	Year	2011	Publication	13th International Conference on Multimodal Interaction	Abbreviated Journal
	Volume		Issue		Pages	393-400
	Keywords	Pedestrian Detection; Human detection; Virtual; Domain Adaptation; Active Learning
	Abstract	Image based human detection is of paramount interest due to its potential applications in fields such as advanced driving assistance, surveillance and media analysis. However, even detecting non-occluded standing humans remains a challenge of intensive research. The most promising human detectors rely on classifiers developed in the discriminative paradigm, i.e., trained with labelled samples. However, labeling is a manual intensive step, especially in cases like human detection where it is necessary to provide at least bounding boxes framing the humans for training. To overcome such problem, some authors have proposed the use of a virtual world where the labels of the different objects are obtained automatically. This means that the human models (classifiers) are learnt using the appearance of rendered images, i.e., using realistic computer graphics. Later, these models are used for human detection in images of the real world. The results of this technique are surprisingly good. However, these are not always as good as the classical approach of training and testing with data coming from the same camera, or similar ones. Accordingly, in this paper we address the challenge of using a virtual world for gathering (while playing a videogame) a large amount of automatically labelled samples (virtual humans and background) and then training a classifier that performs equal, in real-world images, than the one obtained by equally training from manually labelled real-world samples. For doing that, we cast the problem as one of domain adaptation. In doing so, we assume that a small amount of manually labelled samples from real-world images is required. To collect these labelled samples we propose a non-standard active learning technique. Therefore, ultimately our human model is learnt by the combination of virtual and real world labelled samples (Fig. 1), which has not been done before. We present quantitative results showing that this approach is valid.
	Address	Alicante, Spain
	Corporate Author				Thesis
	Publisher	ACM DL	Place of Publication	New York, NY, USA, USA	Editor
	Language	English	Summary Language	English	Original Title	Virtual Worlds and Active Learning for Human Detection
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-1-4503-0641-6	Medium
	Area		Expedition		Conference	ICMI
	Notes	ADAS			Approved	yes
	Call Number	ADAS @ adas @ VLP2011a			Serial	1683
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	Author	Naveen Onkarappa; Angel Sappa
	Title	Space Variant Representations for Mobile Platform Vision Applications			Type	Conference Article
	Year	2011	Publication	14th International Conference on Computer Analysis of Images and Patterns	Abbreviated Journal
	Volume	6855	Issue	II	Pages	146-154
	Keywords
	Abstract	The log-polar space variant representation, motivated by biological vision, has been widely studied in the literature. Its data reduction and invariance properties made it useful in many vision applications. However, due to its nature, it fails in preserving features in the periphery. In the current work, as an attempt to overcome this problem, we propose a novel space-variant representation. It is evaluated and proved to be better than the log-polar representation in preserving the peripheral information, crucial for on-board mobile vision applications. The evaluation is performed by comparing log-polar and the proposed representation once they are used for estimating dense optical flow.
	Address	Seville, Spain
	Corporate Author				Thesis
	Publisher	Springer Berlin Heidelberg	Place of Publication		Editor	P. Real, D. Diaz, H. Molina, A. Berciano, W. Kropatsch
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	0302-9743	ISBN	978-3-642-23677-8	Medium
	Area		Expedition		Conference	CAIP
	Notes	ADAS			Approved	no
	Call Number	NaS2011; ADAS @ adas @			Serial	1686
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	Author	Debora Gil; Agnes Borras; Manuel Ballester; Francesc Carreras; Ruth Aris; Manuel Vazquez; Enric Marti; Ferran Poveda
	Title	MIOCARDIA: Integrating cardiac function and muscular architecture for a better diagnosis			Type	Conference Article
	Year	2011	Publication	14th International Symposium on Applied Sciences in Biomedical and Communication Technologies	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract	Deep understanding of myocardial structure of the heart would unravel crucial knowledge for clinical and medical procedures. The MIOCARDIA project is a multidisciplinary project in cooperation with l'Hospital de la Santa Creu i de Sant Pau, Clinica la Creu Blanca and Barcelona Supercomputing Center. The ultimate goal of this project is defining a computational model of the myocardium. The model takes into account the deep interrelation between the anatomy and the mechanics of the heart. The paper explains the workflow of the MIOCARDIA project. It also introduces a multiresolution reconstruction technique based on DT-MRI streamlining for simplified global myocardial model generation. Our reconstructions can restore the most complex myocardial structures and provides evidences of a global helical organization.
	Address	Barcelona; Spain
	Corporate Author	Association for Computing Machinery			Thesis
	Publisher		Place of Publication	Barcelona, Spain	Editor	Association for Computing Machinery
	Language	english	Summary Language	english	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-1-4503-0913-4	Medium
	Area		Expedition		Conference	ISABEL
	Notes	IAM			Approved	no
	Call Number	IAM @ iam @ GGB2011			Serial	1691
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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	Jorge Bernal; F. Javier Sanchez; Fernando Vilariño
	Title	A Region Segmentation Method for Colonoscopy Images Using a Model of Polyp Appearance			Type	Conference Article
	Year	2011	Publication	5th Iberian Conference on Pattern Recognition and Image Analysis	Abbreviated Journal
	Volume	6669	Issue		Pages	134-143
	Keywords	Colonoscopy, Polyp Detection, Region Merging, Region Segmentation.
	Abstract	This work aims at the segmentation of colonoscopy images into a minimum number of informative regions. Our method performs in a way such, if a polyp is present in the image, it will be exclusively and totally contained in a single region. This result can be used in later stages to classify regions as polyp-containing candidates. The output of the algorithm also defines which regions can be considered as non-informative. The algorithm starts with a high number of initial regions and merges them taking into account the model of polyp appearance obtained from available data. The results show that our segmentations of polyp regions are more accurate than state-of-the-art methods.
	Address	Las Palmas de Gran Canaria, June 2011
	Corporate Author	SpringerLink			Thesis
	Publisher		Place of Publication		Editor	Vitrià, Jordi and Sanches, João and Hernández, Mario
	Language		Summary Language		Original Title
	Series Editor		Series Title	Lecture Notes in Computer Science	Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-3-642-21256-7	Medium
	Area	800	Expedition		Conference	IbPRIA
	Notes	MV;SIAI			Approved	no
	Call Number	IAM @ iam @ BSV2011c			Serial	1696
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	Author	Jorge Bernal; F. Javier Sanchez; Fernando Vilariño
	Title	Integration of Valley Orientation Distribution for Polyp Region Identification in Colonoscopy			Type	Conference Article
	Year	2011	Publication	In MICCAI 2011 Workshop on Computational and Clinical Applications in Abdominal Imaging	Abbreviated Journal
	Volume	6668	Issue		Pages	76-83
	Keywords
	Abstract	This work presents a region descriptor based on the integration of the information that the depth of valleys image provides. The depth of valleys image is based on the presence of intensity valleys around polyps due to the image acquisition. Our proposed method consists of defining, for each point, a series of radial sectors around it and then accumulates the maxima of the depth of valleys image only if the orientation of the intensity valley coincides with the orientation of the sector above. We apply our descriptor to a prior segmentation of the images and we present promising results on polyp detection, outperforming other approaches that also integrate depth of valleys information.
	Address	Toronto, Canada
	Corporate Author				Thesis
	Publisher	Springer Link	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title	Lecture Notes in Computer Science	Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area	800	Expedition		Conference	ABI
	Notes	MV;SIAI			Approved	no
	Call Number	IAM @ iam @ BSV2011d			Serial	1698
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	Author	Jorge Bernal; F. Javier Sanchez; Fernando Vilariño
	Title	Depth of Valleys Accumulation Algorithm for Object Detection			Type	Conference Article
	Year	2011	Publication	14th Congrès Català en Intel·ligencia Artificial	Abbreviated Journal
	Volume	1	Issue	1	Pages	71-80
	Keywords	Object Recognition, Object Region Identification, Image Analysis, Image Processing
	Abstract	This work aims at detecting in which regions the objects in the image are by using information about the intensity of valleys, which appear to surround ob- jects in images where the source of light is in the line of direction than the camera. We present our depth of valleys accumulation method, which consists of two stages: first, the definition of the depth of valleys image which combines the output of a ridges and valleys detector with the morphological gradient to measure how deep is a point inside a valley and second, an algorithm that denotes points of the image as interior to objects those which are inside complete or incomplete boundaries in the depth of valleys image. To evaluate the performance of our method we have tested it on several application domains. Our results on object region identification are promising, specially in the field of polyp detection in colonoscopy videos, and we also show its applicability in different areas.
	Address	Lleida
	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	978-1-60750-841-0	Medium
	Area	800	Expedition		Conference	CCIA
	Notes	MV;SIAI			Approved	no
	Call Number	IAM @ iam @ BSV2011b			Serial	1699
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	Author	Farhan Riaz; Fernando Vilariño; Mario Dinis-Ribeiro; Miguel Coimbraln
	Title	Identifying Potentially Cancerous Tissues in Chromoendoscopy Images			Type	Conference Article
	Year	2011	Publication	5th Iberian Conference on Pattern Recognition and Image Analysis	Abbreviated Journal
	Volume	6669	Issue		Pages	709-716
	Keywords	Endoscopy, Computer Assisted Diagnosis, Gradient.
	Abstract	The dynamics of image acquisition conditions for gastroenterology imaging scenarios pose novel challenges for automatic computer assisted decision systems. Such systems should have the ability to mimic the tissue characterization of the physicians. In this paper, our objective is to compare some feature extraction methods to classify a Chromoendoscopy image into two different classes: Normal and Potentially cancerous. Results show that LoG filters generally give best classification accuracy among the other feature extraction methods considered.
	Address	Las Palmas de Gran Canaria. Spain
	Corporate Author				Thesis
	Publisher	Springer	Place of Publication	Berlin	Editor	J. Vitria, J.M. Sanches, and M. Hernandez
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-3-642-21256-7	Medium
	Area	800	Expedition		Conference	IbPRIA
	Notes	MV;SIAI			Approved	no
	Call Number	Admin @ si @ RVD2011; IAM @ iam @ RVD2011			Serial	1726
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	Author	Mario Rojas; David Masip; Jordi Vitria
	Title	Automatic Detection of Facial Feature Points via HOGs and Geometric Prior Models			Type	Conference Article
	Year	2011	Publication	5th Iberian Conference on Pattern Recognition and Image Analysis	Abbreviated Journal
	Volume	6669	Issue		Pages	371-378
	Keywords
	Abstract	Most applications dealing with problems involving the face require a robust estimation of the facial salient points. Nevertheless, this estimation is not usually an automated preprocessing step in applications dealing with facial expression recognition. In this paper we present a simple method to detect facial salient points in the face. It is based on a prior Point Distribution Model and a robust object descriptor. The model learns the distribution of the points from the training data, as well as the amount of variation in location each point exhibits. Using this model, we reduce the search areas to look for each point. In addition, we also exploit the global consistency of the points constellation, increasing the detection accuracy. The method was tested on two separate data sets and the results, in some cases, outperform the state of the art.
	Address	Las Palmas de Gran Canaria. Spain
	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	978-3-642-21256-7	Medium
	Area		Expedition		Conference	IbPRIA
	Notes	OR;MV			Approved	no
	Call Number	Admin @ si @ RMV2011a			Serial	1731
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	Author	Jon Almazan; Ernest Valveny; Alicia Fornes
	Title	Deforming the Blurred Shape Model for Shape Description and Recognition			Type	Conference Article
	Year	2011	Publication	5th Iberian Conference on Pattern Recognition and Image Analysis	Abbreviated Journal
	Volume	6669	Issue		Pages	1-8
	Keywords
	Abstract	This paper presents a new model for the description and recognition of distorted shapes, where the image is represented by a pixel density distribution based on the Blurred Shape Model combined with a non-linear image deformation model. This leads to an adaptive structure able to capture elastic deformations in shapes. This method has been evaluated using thee different datasets where deformations are present, showing the robustness and good performance of the new model. Moreover, we show that incorporating deformation and flexibility, the new model outperforms the BSM approach when classifying shapes with high variability of appearance.
	Address	Las Palmas de Gran Canaria. Spain
	Corporate Author				Thesis
	Publisher	Springer-Verlag	Place of Publication	Berlin	Editor	Jordi Vitria; Joao Miguel Raposo; Mario Hernandez
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	IbPRIA
	Notes	DAG;			Approved	no
	Call Number	Admin @ si @ AVF2011			Serial	1732
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	Author	Maria Vanrell; Naila Murray; Robert Benavente; C. Alejandro Parraga; Xavier Otazu; Ramon Baldrich
	Title	Perception Based Representations for Computational Colour			Type	Conference Article
	Year	2011	Publication	3rd International Workshop on Computational Color Imaging	Abbreviated Journal
	Volume	6626	Issue		Pages	16-30
	Keywords	colour perception, induction, naming, psychophysical data, saliency, segmentation
	Abstract	The perceived colour of a stimulus is dependent on multiple factors stemming out either from the context of the stimulus or idiosyncrasies of the observer. The complexity involved in combining these multiple effects is the main reason for the gap between classical calibrated colour spaces from colour science and colour representations used in computer vision, where colour is just one more visual cue immersed in a digital image where surfaces, shadows and illuminants interact seemingly out of control. With the aim to advance a few steps towards bridging this gap we present some results on computational representations of colour for computer vision. They have been developed by introducing perceptual considerations derived from the interaction of the colour of a point with its context. We show some techniques to represent the colour of a point influenced by assimilation and contrast effects due to the image surround and we show some results on how colour saliency can be derived in real images. We outline a model for automatic assignment of colour names to image points directly trained on psychophysical data. We show how colour segments can be perceptually grouped in the image by imposing shading coherence in the colour space.
	Address	Milan, Italy
	Corporate Author				Thesis
	Publisher	Springer-Verlag	Place of Publication		Editor	Raimondo Schettini, Shoji Tominaga, Alain Trémeau
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-3-642-20403-6	Medium
	Area		Expedition		Conference	CCIW
	Notes	CIC			Approved	no
	Call Number	Admin @ si @ VMB2011			Serial	1733
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	Author	Michal Drozdzal; Santiago Segui; Carolina Malagelada; Fernando Azpiroz; Jordi Vitria; Petia Radeva
	Title	Interactive Labeling of WCE Images			Type	Conference Article
	Year	2011	Publication	5th Iberian Conference on Pattern Recognition and Image Analysis	Abbreviated Journal
	Volume	6669	Issue		Pages	143-150
	Keywords
	Abstract	A high quality labeled training set is necessary for any supervised machine learning algorithm. Labeling of the data can be a very expensive process, specially while dealing with data of high variability and complexity. A good example of such data are the videos from Wireless Capsule Endoscopy. Building a representative WCE data set means many videos to be labeled by an expert. The problem that occurs is the data diversity, in the space of the features, from different WCE studies. That means that when new data arrives it is highly probable that it will not be represented in the training set, thus getting a high probability of performing an error when applying machine learning schemes. In this paper an interactive labeling scheme that allows reducing expert effort in the labeling process is presented. It is shown that the number of human interventions can be significantly reduced. The proposed system allows the annotation of informative/non-informative frames of the WCE video with less than 100 clicks
	Address	Las Palmas de Gran Canaria. Spain
	Corporate Author				Thesis
	Publisher	Springer	Place of Publication		Editor	Vitria, Jordi; Sanches, João Miguel Raposo; Hernández, Mario
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	IbPRIA
	Notes	MILAB;OR;MV			Approved	no
	Call Number	Admin @ si @ DSM2011			Serial	1734
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	Author	Pierluigi Casale; Oriol Pujol; Petia Radeva
	Title	Human Activity Recognition from Accelerometer Data using a Wearable Device			Type	Conference Article
	Year	2011	Publication	5th Iberian Conference on Pattern Recognition and Image Analysis	Abbreviated Journal
	Volume	6669	Issue		Pages	289-296
	Keywords
	Abstract	Activity Recognition is an emerging field of research, born from the larger fields of ubiquitous computing, context-aware computing and multimedia. Recently, recognizing everyday life activities becomes one of the challenges for pervasive computing. In our work, we developed a novel wearable system easy to use and comfortable to bring. Our wearable system is based on a new set of 20 computationally efficient features and the Random Forest classifier. We obtain very encouraging results with classification accuracy of human activities recognition of up to 94%.
	Address	Las Palmas de Gran Canaria. Spain
	Corporate Author				Thesis
	Publisher	Springer Berlin Heidelberg	Place of Publication		Editor	Vitria, Jordi; Sanches, João Miguel Raposo; Hernández, Mario
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN	0302-9743	ISBN	978-3-642-21256-7	Medium
	Area		Expedition		Conference	IbPRIA
	Notes	MILAB;HuPBA			Approved	no
	Call Number	Admin @ si @ CPR2011a			Serial	1735
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