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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	Miguel Reyes; Albert Clapes; Jose Ramirez; Juan R Revilla; Sergio Escalera
	Title	Automatic Digital Biometry Analysis based on Depth Maps			Type	Journal Article
	Year	2013	Publication	Computers in Industry	Abbreviated Journal	COMPUTIND
	Volume	64	Issue	9	Pages	1316-1325
	Keywords	Multi-modal data fusion; Depth maps; Posture analysis; Anthropometric data; Musculo-skeletal disorders; Gesture analysis
	Abstract	World Health Organization estimates that 80% of the world population is affected by back-related disorders during his life. Current practices to analyze musculo-skeletal disorders (MSDs) are expensive, subjective, and invasive. In this work, we propose a tool for static body posture analysis and dynamic range of movement estimation of the skeleton joints based on 3D anthropometric information from multi-modal data. Given a set of keypoints, RGB and depth data are aligned, depth surface is reconstructed, keypoints are matched, and accurate measurements about posture and spinal curvature are computed. Given a set of joints, range of movement measurements is also obtained. Moreover, gesture recognition based on joint movements is performed to look for the correctness in the development of physical exercises. The system shows high precision and reliable measurements, being useful for posture reeducation purposes to prevent MSDs, as well as tracking the posture evolution of patients in rehabilitation treatments.
	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	HuPBA;MILAB			Approved	no
	Call Number	Admin @ si @ RCR2013			Serial	2252
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	Author	Albert Clapes; Miguel Reyes; Sergio Escalera
	Title	Multi-modal User Identification and Object Recognition Surveillance System			Type	Journal Article
	Year	2013	Publication	Pattern Recognition Letters	Abbreviated Journal	PRL
	Volume	34	Issue	7	Pages	799-808
	Keywords	Multi-modal RGB-Depth data analysis; User identification; Object recognition; Intelligent surveillance; Visual features; Statistical learning
	Abstract	We propose an automatic surveillance system for user identification and object recognition based on multi-modal RGB-Depth data analysis. We model a RGBD environment learning a pixel-based background Gaussian distribution. Then, user and object candidate regions are detected and recognized using robust statistical approaches. The system robustly recognizes users and updates the system in an online way, identifying and detecting new actors in the scene. Moreover, segmented objects are described, matched, recognized, and updated online using view-point 3D descriptions, being robust to partial occlusions and local 3D viewpoint rotations. Finally, the system saves the historic of user–object assignments, being specially useful for surveillance scenarios. The system has been evaluated on a novel data set containing different indoor/outdoor scenarios, objects, and users, showing accurate recognition and better performance than standard state-of-the-art approaches.
	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	HUPBA; 600.046; 605.203;MILAB			Approved	no
	Call Number	Admin @ si @ CRE2013			Serial	2248
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	Author	Fernando Barrera; Felipe Lumbreras; Angel Sappa
	Title	Multispectral Piecewise Planar Stereo using Manhattan-World Assumption			Type	Journal Article
	Year	2013	Publication	Pattern Recognition Letters	Abbreviated Journal	PRL
	Volume	34	Issue	1	Pages	52-61
	Keywords	Multispectral stereo rig; Dense disparity maps from multispectral stereo; Color and infrared images
	Abstract	This paper proposes a new framework for extracting dense disparity maps from a multispectral stereo rig. The system is constructed with an infrared and a color camera. It is intended to explore novel multispectral stereo matching approaches that will allow further extraction of semantic information. The proposed framework consists of three stages. Firstly, an initial sparse disparity map is generated by using a cost function based on feature matching in a multiresolution scheme. Then, by looking at the color image, a set of planar hypotheses is defined to describe the surfaces on the scene. Finally, the previous stages are combined by reformulating the disparity computation as a global minimization problem. The paper has two main contributions. The first contribution combines mutual information with a shape descriptor based on gradient in a multiresolution scheme. The second contribution, which is based on the Manhattan-world assumption, extracts a dense disparity representation using the graph cut algorithm. Experimental results in outdoor scenarios are provided showing the validity of the proposed framework.
	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	ADAS; 600.054; 600.055; 605.203			Approved	no
	Call Number	Admin @ si @ BLS2013			Serial	2245
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	Author	Olivier Penacchio; Xavier Otazu; Laura Dempere-Marco
	Title	A Neurodynamical Model of Brightness Induction in V1			Type	Journal Article
	Year	2013	Publication	PloS ONE	Abbreviated Journal	Plos
	Volume	8	Issue	5	Pages	e64086
	Keywords
	Abstract	Brightness induction is the modulation of the perceived intensity of an area by the luminance of surrounding areas. Recent neurophysiological evidence suggests that brightness information might be explicitly represented in V1, in contrast to the more common assumption that the striate cortex is an area mostly responsive to sensory information. Here we investigate possible neural mechanisms that offer a plausible explanation for such phenomenon. To this end, a neurodynamical model which is based on neurophysiological evidence and focuses on the part of V1 responsible for contextual influences is presented. The proposed computational model successfully accounts for well known psychophysical effects for static contexts and also for brightness induction in dynamic contexts defined by modulating the luminance of surrounding areas. This work suggests that intra-cortical interactions in V1 could, at least partially, explain brightness induction effects and reveals how a common general architecture may account for several different fundamental processes, such as visual saliency and brightness induction, which emerge early in the visual processing pathway.
	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	CIC			Approved	no
	Call Number	Admin @ si @ POD2013			Serial	2242
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	Author	Sandra Jimenez; Xavier Otazu; Valero Laparra; Jesus Malo
	Title	Chromatic induction and contrast masking: similar models, different goals?			Type	Conference Article
	Year	2013	Publication	Human Vision and Electronic Imaging XVIII	Abbreviated Journal
	Volume	8651	Issue		Pages
	Keywords
	Abstract	Normalization of signals coming from linear sensors is an ubiquitous mechanism of neural adaptation.1 Local interaction between sensors tuned to a particular feature at certain spatial position and neighbor sensors explains a wide range of psychophysical facts including (1) masking of spatial patterns, (2) non-linearities of motion sensors, (3) adaptation of color perception, (4) brightness and chromatic induction, and (5) image quality assessment. Although the above models have formal and qualitative similarities, it does not necessarily mean that the mechanisms involved are pursuing the same statistical goal. For instance, in the case of chromatic mechanisms (disregarding spatial information), different parameters in the normalization give rise to optimal discrimination or adaptation, and different non-linearities may give rise to error minimization or component independence. In the case of spatial sensors (disregarding color information), a number of studies have pointed out the benefits of masking in statistical independence terms. However, such statistical analysis has not been performed for spatio-chromatic induction models where chromatic perception depends on spatial configuration. In this work we investigate whether successful spatio-chromatic induction models,6 increase component independence similarly as previously reported for masking models. Mutual information analysis suggests that seeking an efficient chromatic representation may explain the prevalence of induction effects in spatially simple images. © (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
	Address	San Francisco CA; USA; February 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	HVEI
	Notes	CIC			Approved	no
	Call Number	Admin @ si @ JOL2013			Serial	2240
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	Author	Santiago Segui; Michal Drozdzal; Ekaterina Zaytseva; Carolina Malagelada; Fernando Azpiroz; Petia Radeva; Jordi Vitria
	Title	A new image centrality descriptor for wrinkle frame detection in WCE videos			Type	Conference Article
	Year	2013	Publication	13th IAPR Conference on Machine Vision Applications	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract	Small bowel motility dysfunctions are a widespread functional disorder characterized by abdominal pain and altered bowel habits in the absence of specific and unique organic pathology. Current methods of diagnosis are complex and can only be conducted at some highly specialized referral centers. Wireless Video Capsule Endoscopy (WCE) could be an interesting diagnostic alternative that presents excellent clinical advantages, since it is non-invasive and can be conducted by non specialists. The purpose of this work is to present a new method for the detection of wrinkle frames in WCE, a critical characteristic to detect one of the main motility events: contractions. The method goes beyond the use of one of the classical image feature, the Histogram
	Address	Kyoto; Japan; May 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	MVA
	Notes	OR; MILAB; 600.046;MV			Approved	no
	Call Number	Admin @ si @ SDZ2013			Serial	2239
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	Author	Xavier Baro; David Masip; Elena Planas; Julia Minguillon
	Title	PeLP: Plataforma para el Aprendizaje de Lenguajes de Programación			Type	Miscellaneous
	Year	2013	Publication	XV Jornadas de Enseñanza Universitaria de la Informatica	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	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	JENUI
	Notes	OR;HuPBA;MV			Approved	no
	Call Number	Admin @ si @ BMP2013			Serial	2237
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	Author	Victor Borjas; Jordi Vitria; Petia Radeva
	Title	Gradient Histogram Background Modeling for People Detection in Stationary Camera Environments			Type	Conference Article
	Year	2013	Publication	13th IAPR Conference on Machine Vision Applications	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract	Best Poster AwardOne of the big challenges of today person detectors is the decreasing of the false positive rate. In this paper, we propose a novel framework to customize person detectors in static camera scenarios in order to reduce this rate. This scheme includes background modeling for subtraction based on gradient histograms and Mean-Shift clustering. Our experiments show that the detection improved compared to using only the output from the pedestrian detector reducing 87% of the false positives and therefore the overall precision of the detection was increased signicantly.
	Address	Kyoto; Japan; May 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	MVA
	Notes	OR; MILAB;MV			Approved	no
	Call Number	BVR2013			Serial	2238
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	Author	Fadi Dornaika; Bogdan Raducanu
	Title	Out-of-Sample Embedding for Manifold Learning Applied to Face Recognition			Type	Conference Article
	Year	2013	Publication	IEEE International Workshop on Analysis and Modeling of Faces and Gestures	Abbreviated Journal
	Volume		Issue		Pages	862-868
	Keywords
	Abstract	Manifold learning techniques are affected by two critical aspects: (i) the design of the adjacency graphs, and (ii) the embedding of new test data---the out-of-sample problem. For the first aspect, the proposed schemes were heuristically driven. For the second aspect, the difficulty resides in finding an accurate mapping that transfers unseen data samples into an existing manifold. Past works addressing these two aspects were heavily parametric in the sense that the optimal performance is only reached for a suitable parameter choice that should be known in advance. In this paper, we demonstrate that sparse coding theory not only serves for automatic graph reconstruction as shown in recent works, but also represents an accurate alternative for out-of-sample embedding. Considering for a case study the Laplacian Eigenmaps, we applied our method to the face recognition problem. To evaluate the effectiveness of the proposed out-of-sample embedding, experiments are conducted using the k-nearest neighbor (KNN) and Kernel Support Vector Machines (KSVM) classifiers on four public face databases. The experimental results show that the proposed model is able to achieve high categorization effectiveness as well as high consistency with non-linear embeddings/manifolds obtained in batch modes.
	Address	Portland; USA; 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		Medium
	Area		Expedition		Conference	CVPRW
	Notes	OR; 600.046;MV			Approved	no
	Call Number	Admin @ si @ DoR2013			Serial	2236
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	Author	Marina Alberti; Simone Balocco; Xavier Carrillo; J. Mauri; Petia Radeva
	Title	Automatic non-rigid temporal alignment of IVUS sequences: method and quantitative validation			Type	Journal Article
	Year	2013	Publication	Ultrasound in Medicine and Biology	Abbreviated Journal	UMB
	Volume	39	Issue	9	Pages	1698-712
	Keywords	Intravascular ultrasound; Dynamic time warping; Non-rigid alignment; Sequence matching; Partial overlapping strategy
	Abstract	Clinical studies on atherosclerosis regression/progression performed by intravascular ultrasound analysis would benefit from accurate alignment of sequences of the same patient before and after clinical interventions and at follow-up. In this article, a methodology for automatic alignment of intravascular ultrasound sequences based on the dynamic time warping technique is proposed. The non-rigid alignment is adapted to the specific task by applying it to multidimensional signals describing the morphologic content of the vessel. Moreover, dynamic time warping is embedded into a framework comprising a strategy to address partial overlapping between acquisitions and a term that regularizes non-physiologic temporal compression/expansion of the sequences. Extensive validation is performed on both synthetic and in vivo data. The proposed method reaches alignment errors of approximately 0.43 mm for pairs of sequences acquired during the same intervention phase and 0.77 mm for pairs of sequences acquired at successive intervention stages.
	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			Approved	no
	Call Number	Admin @ si @ ABC2013			Serial	2313
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	Author	Simone Balocco; Carlo Gatta; Francesco Ciompi; A. Wahle; Petia Radeva; S. Carlier; G. Unal; E. Sanidas; J. Mauri; X. Carillo; T. Kovarnik; C. Wang; H. Chen; T. P. Exarchos; D. I. Fotiadis; F. Destrempes; G. Cloutier; Oriol Pujol; Marina Alberti; E. G. Mendizabal-Ruiz; M. Rivera; T. Aksoy; R. W. Downe; I. A. Kakadiaris
	Title	Standardized evaluation methodology and reference database for evaluating IVUS image segmentation			Type	Journal Article
	Year	2014	Publication	Computerized Medical Imaging and Graphics	Abbreviated Journal	CMIG
	Volume	38	Issue	2	Pages	70-90
	Keywords	IVUS (intravascular ultrasound); Evaluation framework; Algorithm comparison; Image segmentation
	Abstract	This paper describes an evaluation framework that allows a standardized and quantitative comparison of IVUS lumen and media segmentation algorithms. This framework has been introduced at the MICCAI 2011 Computing and Visualization for (Intra)Vascular Imaging (CVII) workshop, comparing the results of eight teams that participated. We describe the available data-base comprising of multi-center, multi-vendor and multi-frequency IVUS datasets, their acquisition, the creation of the reference standard and the evaluation measures. The approaches address segmentation of the lumen, the media, or both borders; semi- or fully-automatic operation; and 2-D vs. 3-D methodology. Three performance measures for quantitative analysis have been proposed. The results of the evaluation indicate that segmentation of the vessel lumen and media is possible with an accuracy that is comparable to manual annotation when semi-automatic methods are used, as well as encouraging results can be obtained also in case of fully-automatic segmentation. The analysis performed in this paper also highlights the challenges in IVUS segmentation that remains to be solved.
	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; LAMP; HuPBA; 600.046; 600.063; 600.079			Approved	no
	Call Number	Admin @ si @ BGC2013			Serial	2314
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	Author	Francisco Javier Orozco; Ognjen Rudovic; Jordi Gonzalez; Maja Pantic
	Title	Hierarchical On-line Appearance-Based Tracking for 3D Head Pose, Eyebrows, Lips, Eyelids and Irises			Type	Journal Article
	Year	2013	Publication	Image and Vision Computing	Abbreviated Journal	IMAVIS
	Volume	31	Issue	4	Pages	322-340
	Keywords	On-line appearance models; Levenberg–Marquardt algorithm; Line-search optimization; 3D face tracking; Facial action tracking; Eyelid tracking; Iris tracking
	Abstract	In this paper, we propose an On-line Appearance-Based Tracker (OABT) for simultaneous tracking of 3D head pose, lips, eyebrows, eyelids and irises in monocular video sequences. In contrast to previously proposed tracking approaches, which deal with face and gaze tracking separately, our OABT can also be used for eyelid and iris tracking, as well as 3D head pose, lips and eyebrows facial actions tracking. Furthermore, our approach applies an on-line learning of changes in the appearance of the tracked target. Hence, the prior training of appearance models, which usually requires a large amount of labeled facial images, is avoided. Moreover, the proposed method is built upon a hierarchical combination of three OABTs, which are optimized using a Levenberg–Marquardt Algorithm (LMA) enhanced with line-search procedures. This, in turn, makes the proposed method robust to changes in lighting conditions, occlusions and translucent textures, as evidenced by our experiments. Finally, the proposed method achieves head and facial actions tracking in real-time.
	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	ISE; 605.203; 302.012; 302.018; 600.049			Approved	no
	Call Number	ORG2013			Serial	2221
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	Author	Carles Sanchez; Debora Gil; Antoni Rosell; Albert Andaluz; F. Javier Sanchez
	Title	Segmentation of Tracheal Rings in Videobronchoscopy combining Geometry and Appearance			Type	Conference Article
	Year	2013	Publication	Proceedings of the International Conference on Computer Vision Theory and Applications	Abbreviated Journal
	Volume	1	Issue		Pages	153--161
	Keywords	Video-bronchoscopy, tracheal ring segmentation, trachea geometric and appearance model
	Abstract	Videobronchoscopy is a medical imaging technique that allows interactive navigation inside the respiratory pathways and minimal invasive interventions. Tracheal procedures are ordinary interventions that require measurement of the percentage of obstructed pathway for injury (stenosis) assessment. Visual assessment of stenosis in videobronchoscopic sequences requires high expertise of trachea anatomy and is prone to human error. Accurate detection of tracheal rings is the basis for automated estimation of the size of stenosed trachea. Processing of videobronchoscopic images acquired at the operating room is a challenging task due to the wide range of artifacts and acquisition conditions. We present a model of the geometric-appearance of tracheal rings for its detection in videobronchoscopic videos. Experiments on sequences acquired at the operating room, show a performance close to inter-observer variability
	Address	Barcelona; February 2013
	Corporate Author				Thesis
	Publisher	SciTePress	Place of Publication	Portugal	Editor	Sebastiano Battiato and José Braz
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-989-8565-47-1	Medium
	Area	800	Expedition		Conference	VISAPP
	Notes	IAM;MV; 600.044; 600.047; 600.060; 605.203			Approved	no
	Call Number	IAM @ iam @ SGR2013			Serial	2123
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	Author	Josep Llados; Marçal Rusiñol; Alicia Fornes; David Fernandez; Anjan Dutta
	Title	On the Influence of Word Representations for Handwritten Word Spotting in Historical Documents			Type	Journal Article
	Year	2012	Publication	International Journal of Pattern Recognition and Artificial Intelligence	Abbreviated Journal	IJPRAI
	Volume	26	Issue	5	Pages	1263002-126027
	Keywords	Handwriting recognition; word spotting; historical documents; feature representation; shape descriptors Read More: http://www.worldscientific.com/doi/abs/10.1142/S0218001412630025
	Abstract	0,624 JCR Word spotting is the process of retrieving all instances of a queried keyword from a digital library of document images. In this paper we evaluate the performance of different word descriptors to assess the advantages and disadvantages of statistical and structural models in a framework of query-by-example word spotting in historical documents. We compare four word representation models, namely sequence alignment using DTW as a baseline reference, a bag of visual words approach as statistical model, a pseudo-structural model based on a Loci features representation, and a structural approach where words are represented by graphs. The four approaches have been tested with two collections of historical data: the George Washington database and the marriage records from the Barcelona Cathedral. We experimentally demonstrate that statistical representations generally give a better performance, however it cannot be neglected that large descriptors are difficult to be implemented in a retrieval scenario where word spotting requires the indexation of data with million word images.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	DAG			Approved	no
	Call Number	Admin @ si @ LRF2012			Serial	2128
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