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	Author	German Ros; J. Guerrero; Angel Sappa; Antonio Lopez
	Title	VSLAM pose initialization via Lie groups and Lie algebras optimization			Type	Conference Article
	Year	2013	Publication	Proceedings of IEEE International Conference on Robotics and Automation	Abbreviated Journal
	Volume		Issue		Pages	5740 - 5747
	Keywords	SLAM
	Abstract	We present a novel technique for estimating initial 3D poses in the context of localization and Visual SLAM problems. The presented approach can deal with noise, outliers and a large amount of input data and still performs in real time in a standard CPU. Our method produces solutions with an accuracy comparable to those produced by RANSAC but can be much faster when the percentage of outliers is high or for large amounts of input data. On the current work we propose to formulate the pose estimation as an optimization problem on Lie groups, considering their manifold structure as well as their associated Lie algebras. This allows us to perform a fast and simple optimization at the same time that conserve all the constraints imposed by the Lie group SE(3). Additionally, we present several key design concepts related with the cost function and its Jacobian; aspects that are critical for the good performance of the algorithm.
	Address	Karlsruhe; Germany; 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	1050-4729	ISBN	978-1-4673-5641-1	Medium
	Area		Expedition		Conference	ICRA
	Notes	ADAS; 600.054; 600.055; 600.057			Approved	no
	Call Number	Admin @ si @ RGS2013a; ADAS @ adas @			Serial	2225
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	Author	David Aldavert; Marçal Rusiñol; Ricardo Toledo; Josep Llados
	Title	Integrating Visual and Textual Cues for Query-by-String Word Spotting			Type	Conference Article
	Year	2013	Publication	12th International Conference on Document Analysis and Recognition	Abbreviated Journal
	Volume		Issue		Pages	511 - 515
	Keywords
	Abstract	In this paper, we present a word spotting framework that follows the query-by-string paradigm where word images are represented both by textual and visual representations. The textual representation is formulated in terms of character $n$-grams while the visual one is based on the bag-of-visual-words scheme. These two representations are merged together and projected to a sub-vector space. This transform allows to, given a textual query, retrieve word instances that were only represented by the visual modality. Moreover, this statistical representation can be used together with state-of-the-art indexation structures in order to deal with large-scale scenarios. The proposed method is evaluated using a collection of historical documents outperforming state-of-the-art performances.
	Address	Washington; USA; August 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	1520-5363	ISBN		Medium
	Area		Expedition		Conference	ICDAR
	Notes	DAG; ADAS; 600.045; 600.055; 600.061			Approved	no
	Call Number	Admin @ si @ ART2013			Serial	2224
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	Author	Ariel Amato; Ivan Huerta; Mikhail Mozerov; Xavier Roca; Jordi Gonzalez
	Title	Moving Cast Shadows Detection Methods for Video Surveillance Applications			Type	Book Chapter
	Year	2014	Publication	Augmented Vision and Reality	Abbreviated Journal
	Volume	6	Issue		Pages	23-47
	Keywords
	Abstract	Moving cast shadows are a major concern in today’s performance from broad range of many vision-based surveillance applications because they highly difficult the object classification task. Several shadow detection methods have been reported in the literature during the last years. They are mainly divided into two domains. One usually works with static images, whereas the second one uses image sequences, namely video content. In spite of the fact that both cases can be analogously analyzed, there is a difference in the application field. The first case, shadow detection methods can be exploited in order to obtain additional geometric and semantic cues about shape and position of its casting object (‘shape from shadows’) as well as the localization of the light source. While in the second one, the main purpose is usually change detection, scene matching or surveillance (usually in a background subtraction context). Shadows can in fact modify in a negative way the shape and color of the target object and therefore affect the performance of scene analysis and interpretation in many applications. This chapter wills mainly reviews shadow detection methods as well as their taxonomies related with the second case, thus aiming at those shadows which are associated with moving objects (moving shadows).
	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	2190-5916	ISBN	978-3-642-37840-9	Medium
	Area		Expedition		Conference
	Notes	ISE; 605.203; 600.049; 302.018; 302.012; 600.078			Approved	no
	Call Number	Admin @ si @ AHM2014			Serial	2223
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	Author	Marc Castello; Jordi Gonzalez; Ariel Amato; Pau Baiget; Carles Fernandez; Josep M. Gonfaus; Ramon Mollineda; Marco Pedersoli; Nicolas Perez de la Blanca; Xavier Roca
	Title	Exploiting Multimodal Interaction Techniques for Video-Surveillance			Type	Book Chapter
	Year	2013	Publication	Multimodal Interaction in Image and Video Applications Intelligent Systems Reference Library	Abbreviated Journal
	Volume	48	Issue	8	Pages	135-151
	Keywords
	Abstract	In this paper we present an example of a video surveillance application that exploits Multimodal Interactive (MI) technologies. The main objective of the so-called VID-Hum prototype was to develop a cognitive artificial system for both the detection and description of a particular set of human behaviours arising from real-world events. The main procedure of the prototype described in this chapter entails: (i) adaptation, since the system adapts itself to the most common behaviours (qualitative data) inferred from tracking (quantitative data) thus being able to recognize abnormal behaviors; (ii) feedback, since an advanced interface based on Natural Language understanding allows end-users the communicationwith the prototype by means of conceptual sentences; and (iii) multimodality, since a virtual avatar has been designed to describe what is happening in the scene, based on those textual interpretations generated by the prototype. Thus, the MI methodology has provided an adequate framework for all these cooperating processes.
	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	1868-4394	ISBN	978-3-642-35931-6	Medium
	Area		Expedition		Conference
	Notes	ISE; 605.203; 600.049			Approved	no
	Call Number	CGA2013			Serial	2222
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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	Antonio Hernandez; Miguel Angel Bautista; Xavier Perez Sala; Victor Ponce; Xavier Baro; Oriol Pujol; Cecilio Angulo; Sergio Escalera
	Title	BoVDW: Bag-of-Visual-and-Depth-Words for Gesture Recognition			Type	Conference Article
	Year	2012	Publication	21st International Conference on Pattern Recognition	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract	We present a Bag-of-Visual-and-Depth-Words (BoVDW) model for gesture recognition, an extension of the Bag-of-Visual-Words (BoVW) model, that benefits from the multimodal fusion of visual and depth features. State-of-the-art RGB and depth features, including a new proposed depth descriptor, are analysed and combined in a late fusion fashion. The method is integrated in a continuous gesture recognition pipeline, where Dynamic Time Warping (DTW) algorithm is used to perform prior segmentation of gestures. Results of the method in public data sets, within our gesture recognition pipeline, show better performance in comparison to a standard BoVW model.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	1051-4651	ISBN	978-1-4673-2216-4	Medium
	Area		Expedition		Conference	ICPR
	Notes	HuPBA;MV			Approved	no
	Call Number	Admin @ si @ HBP2012			Serial	2122
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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	Anjan Dutta; Jaume Gibert; Josep Llados; Horst Bunke; Umapada Pal
	Title	Combination of Product Graph and Random Walk Kernel for Symbol Spotting in Graphical Documents			Type	Conference Article
	Year	2012	Publication	21st International Conference on Pattern Recognition	Abbreviated Journal
	Volume		Issue		Pages	1663-1666
	Keywords
	Abstract	This paper explores the utilization of product graph for spotting symbols on graphical documents. Product graph is intended to find the candidate subgraphs or components in the input graph containing the paths similar to the query graph. The acute angle between two edges and their length ratio are considered as the node labels. In a second step, each of the candidate subgraphs in the input graph is assigned with a distance measure computed by a random walk kernel. Actually it is the minimum of the distances of the component to all the components of the model graph. This distance measure is then used to eliminate dissimilar components. The remaining neighboring components are grouped and the grouped zone is considered as a retrieval zone of a symbol similar to the queried one. The entire method works online, i.e., it doesn't need any preprocessing step. The present paper reports the initial results of the method, which are very encouraging.
	Address	Tsukuba, Japan
	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	1051-4651	ISBN	978-1-4673-2216-4	Medium
	Area		Expedition		Conference	ICPR
	Notes	DAG			Approved	no
	Call Number	Admin @ si @ DGL2012			Serial	2125
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	Author	Klaus Broelemann; Anjan Dutta; Xiaoyi Jiang; Josep Llados
	Title	Hierarchical graph representation for symbol spotting in graphical document images			Type	Conference Article
	Year	2012	Publication	Structural, Syntactic, and Statistical Pattern Recognition, Joint IAPR International Workshop	Abbreviated Journal
	Volume	7626	Issue		Pages	529-538
	Keywords
	Abstract	Symbol spotting can be defined as locating given query symbol in a large collection of graphical documents. In this paper we present a hierarchical graph representation for symbols. This representation allows graph matching methods to deal with low-level vectorization errors and, thus, to perform a robust symbol spotting. To show the potential of this approach, we conduct an experiment with the SESYD dataset.
	Address	Miyajima-Itsukushima, Hiroshima
	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	978-3-642-34165-6	Medium
	Area		Expedition		Conference	SSPR&SPR
	Notes	DAG			Approved	no
	Call Number	Admin @ si @ BDJ2012			Serial	2126
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	Author	Javier Vazquez; Robert Benavente; Maria Vanrell
	Title	Naming constraints constancy			Type	Conference Article
	Year	2012	Publication	2nd Joint AVA / BMVA Meeting on Biological and Machine Vision	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract	Different studies have shown that languages from industrialized cultures share a set of 11 basic colour terms: red, green, blue, yellow, pink, purple, brown, orange, black, white, and grey (Berlin & Kay, 1969, Basic Color Terms, University of California Press)( Kay & Regier, 2003, PNAS, 100, 9085-9089). Some of these studies have also reported the best representatives or focal values of each colour (Boynton and Olson, 1990, Vision Res. 30,1311–1317), (Sturges and Whitfield, 1995, CRA, 20:6, 364–376). Some further studies have provided us with fuzzy datasets for color naming by asking human observers to rate colours in terms of membership values (Benavente -et al-, 2006, CRA. 31:1, 48–56,). Recently, a computational model based on these human ratings has been developed (Benavente -et al-, 2008, JOSA-A, 25:10, 2582-2593). This computational model follows a fuzzy approach to assign a colour name to a particular RGB value. For example, a pixel with a value (255,0,0) will be named 'red' with membership 1, while a cyan pixel with a RGB value of (0, 200, 200) will be considered to be 0.5 green and 0.5 blue. In this work, we show how this colour naming paradigm can be applied to different computer vision tasks. In particular, we report results in colour constancy (Vazquez-Corral -et al-, 2012, IEEE TIP, in press) showing that the classical constraints on either illumination or surface reflectance can be substituted by the statistical properties encoded in the colour names. [Supported by projects TIN2010-21771-C02-1, CSD2007-00018].
	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	AV A
	Notes	CIC			Approved	no
	Call Number	Admin @ si @ VBV2012			Serial	2131
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	Author	Xavier Otazu; Olivier Penacchio; Laura Dempere-Marco
	Title	An investigation into plausible neural mechanisms related to the the CIWaM computational model for brightness induction			Type	Conference Article
	Year	2012	Publication	2nd Joint AVA / BMVA Meeting on Biological and Machine Vision	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract	Brightness induction is the modulation of the perceived intensity of an area by the luminance of surrounding areas. From a purely computational perspective, we built a low-level computational model (CIWaM) of early sensory processing based on multi-resolution wavelets with the aim of replicating brightness and colour (Otazu et al., 2010, Journal of Vision, 10(12):5) induction effects. Furthermore, we successfully used the CIWaM architecture to define a computational saliency model (Murray et al, 2011, CVPR, 433-440; Vanrell et al, submitted to AVA/BMVA'12). From a biological perspective, neurophysiological evidence suggests that perceived brightness information may be explicitly represented in V1. In this work we investigate possible neural mechanisms that offer a plausible explanation for such effects. To this end, we consider the model by Z.Li (Li, 1999, Network:Comput. Neural Syst., 10, 187-212) which is based on biological data and focuses on the part of V1 responsible for contextual influences, namely, layer 2-3 pyramidal cells, interneurons, and horizontal intracortical connections. This model has proven to account for phenomena such as visual saliency, which share with brightness induction the relevant effect of contextual influences (the ones modelled by CIWaM). In the proposed model, the input to the network is derived from a complete multiscale and multiorientation wavelet decomposition taken from the computational model (CIWaM). This model successfully accounts for well known pyschophysical effects (among them: the White's and modied White's effects, the Todorovic, Chevreul, achromatic ring patterns, and grating induction effects) for static contexts and also for brigthness induction in dynamic contexts defined by modulating the luminance of surrounding areas. From a methodological point of view, we conclude that the results obtained by the computational model (CIWaM) are compatible with the ones obtained by the neurodynamical model proposed here.
	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	AV A
	Notes	CIC			Approved	no
	Call Number	Admin @ si @ OPD2012a			Serial	2132
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	Author	Thanh Ha Do; Salvatore Tabbone; Oriol Ramos Terrades
	Title	Text/graphic separation using a sparse representation with multi-learned dictionaries			Type	Conference Article
	Year	2012	Publication	21st International Conference on Pattern Recognition	Abbreviated Journal
	Volume		Issue		Pages
	Keywords	Graphics Recognition; Layout Analysis; Document Understandin
	Abstract	In this paper, we propose a new approach to extract text regions from graphical documents. In our method, we first empirically construct two sequences of learned dictionaries for the text and graphical parts respectively. Then, we compute the sparse representations of all different sizes and non-overlapped document patches in these learned dictionaries. Based on these representations, each patch can be classified into the text or graphic category by comparing its reconstruction errors. Same-sized patches in one category are then merged together to define the corresponding text or graphic layers which are combined to createfinal text/graphic layer. Finally, in a post-processing step, text regions are further filtered out by using some learned thresholds.
	Address	Tsukuba
	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	ICPR
	Notes	DAG			Approved	no
	Call Number	Admin @ si @ DTR2012a			Serial	2135
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	Author	Thanh Ha Do; Salvatore Tabbone; Oriol Ramos Terrades
	Title	Noise suppression over bi-level graphical documents using a sparse representation			Type	Conference Article
	Year	2012	Publication	Colloque International Francophone sur l'Écrit et le Document	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	Address	Bordeaux
	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	CIFED
	Notes	DAG			Approved	no
	Call Number	Admin @ si @ DTR2012b			Serial	2136
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	Author	Adriana Romero; Simeon Petkov; Carlo Gatta; M.Sabate; Petia Radeva
	Title	Efficient automatic segmentation of vessels			Type	Conference Article
	Year	2012	Publication	16th Conference on Medical Image Understanding and Analysis	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	Address	Swansea, United Kingdom
	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	MIUA
	Notes	MILAB			Approved	no
	Call Number	Admin @ si @			Serial	2137
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