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	Author	Pau Baiget; Carles Fernandez; Xavier Roca; Jordi Gonzalez
	Title	Generation of Augmented Video Sequences Combining Behavioral Animation and Multi Object Tracking			Type	Journal Article
	Year	2009	Publication	Computer Animation and Virtual Worlds	Abbreviated Journal
	Volume	20	Issue	4	Pages	473–489
	Keywords
	Abstract	In this paper we present a novel approach to generate augmented video sequences in real-time, involving interactions between virtual and real agents in real scenarios. On the one hand, real agent motion is estimated by means of a multi-object tracking algorithm, which determines real objects' position over the scenario for each time step. On the other hand, virtual agents are provided with behavior models considering their interaction with the environment and with other agents. The resulting framework allows to generate video sequences involving behavior-based virtual agents that react to real agent behavior and has applications in education, simulation, and in the game and movie industries. We show the performance of the proposed approach in an indoor and outdoor scenario simulating human and vehicle agents. Copyright © 2009 John Wiley & Sons, Ltd. We present a novel approach to generate augmented video sequences in real-time, involving interactions between virtual and real agents in real scenarios. On the one hand, real agent motion is estimated by means of a multi-object tracking algorithm, which determines real objects' position over the scenario for each time step. On the other hand, virtual agents are provided with behavior models considering their interaction with the environment and with other agents. © 2009 Wiley Periodicals, Inc.
	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	ISE			Approved	no
	Call Number	ISE @ ise @ BFR2009			Serial	1170
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	Author	David Aldavert; Ricardo Toledo; Arnau Ramisa; Ramon Lopez de Mantaras
	Title	Efficient Object Pixel-Level Categorization using Bag of Features: Advances in Visual Computing			Type	Conference Article
	Year	2009	Publication	5th International Symposium on Visual Computing	Abbreviated Journal
	Volume	5875	Issue		Pages	44–55
	Keywords
	Abstract	In this paper we present a pixel-level object categorization method suitable to be applied under real-time constraints. Since pixels are categorized using a bag of features scheme, the major bottleneck of such an approach would be the feature pooling in local histograms of visual words. Therefore, we propose to bypass this time-consuming step and directly obtain the score from a linear Support Vector Machine classifier. This is achieved by creating an integral image of the components of the SVM which can readily obtain the classification score for any image sub-window with only 10 additions and 2 products, regardless of its size. Besides, we evaluated the performance of two efficient feature quantization methods: the Hierarchical K-Means and the Extremely Randomized Forest. All experiments have been done in the Graz02 database, showing comparable, or even better results to related work with a lower computational cost.
	Address	Las Vegas, USA
	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	978-3-642-10330-8	Medium
	Area		Expedition		Conference	ISVC
	Notes	ADAS			Approved	no
	Call Number	Admin @ si @ ATR2009a			Serial	1246
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	Author	Mathieu Nicolas Delalandre; Jean-Yves Ramel; Ernest Valveny; Muhammad Muzzamil Luqman
	Title	A Performance Characterization Algorithm for Symbol Localization			Type	Conference Article
	Year	2009	Publication	8th IAPR International Workshop on Graphics Recognition	Abbreviated Journal
	Volume		Issue		Pages	3-11
	Keywords
	Abstract	In this paper we present an algorithm for performance characterization of symbol localization systems. This algorithm is aimed to be a more “reliable” and “open” solution to characterize the performance. To achieve that, it exploits only single points as the result of localization and offers the possibility to reconsider the localization results provided by a system. We use the information about context in groundtruth, and overall localization results, to detect the ambiguous localization results. A probability score is computed for each matching between a localization point and a groundtruth region, depending on the spatial distribution of the other regions in the groundtruth. Final characterization is given with detection rate/probability score plots, describing the sets of possible interpretations of the localization results, according to a given confidence rate. We present experimentation details along with the results for the symbol localization system of [1], exploiting a synthetic dataset of architectural floorplans and electrical diagrams (composed of 200 images and 3861 symbols).
	Address	La Rochelle; July 2009
	Corporate Author				Thesis
	Publisher	Springer	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	GREC
	Notes	DAG			Approved	no
	Call Number	DAG @ dag @ DRV2009			Serial	1443
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	Author	Mikhail Mozerov; Ariel Amato; Xavier Roca
	Title	Occlusion Handling in Trinocular Stereo using Composite Disparity Space Image			Type	Conference Article
	Year	2009	Publication	19th International Conference on Computer Graphics and Vision	Abbreviated Journal
	Volume		Issue		Pages	69–73
	Keywords
	Abstract	In this paper we propose a method that smartly improves occlusion handling in stereo matching using trinocular stereo. The main idea is based on the assumption that any occluded region in a matched stereo pair (middle-left images) in general is not occluded in the opposite matched pair (middle-right images). Then two disparity space images (DSI) can be merged in one composite DSI. The proposed integration differs from the known approach that uses a cumulative cost. A dense disparity map is obtained with a global optimization algorithm using the proposed composite DSI. The experimental results are evaluated on the Middlebury data set, showing high performance of the proposed algorithm especially in the occluded regions. One of the top positions in the rank of the Middlebury website confirms the performance of our method to be competitive with the best stereo matching.
	Address	Moscow (Russia)
	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	978-5-317-02975-3	Medium
	Area		Expedition		Conference	GRAPHICON
	Notes	ISE			Approved	no
	Call Number	ISE @ ise @ MAR2009b			Serial	1207
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	Author	Marçal Rusiñol; K. Bertet; Jean-Marc Ogier; Josep Llados
	Title	Symbol Recognition Using a Concept Lattice of Graphical Patterns			Type	Conference Article
	Year	2009	Publication	8th IAPR International Workshop on Graphics Recognition	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract	In this paper we propose a new approach to recognize symbols by the use of a concept lattice. We propose to build a concept lattice in terms of graphical patterns. Each model symbol is decomposed in a set of composing graphical patterns taken as primitives. Each one of these primitives is described by boundary moment invariants. The obtained concept lattice relates which symbolic patterns compose a given graphical symbol. A Hasse diagram is derived from the context and is used to recognize symbols affected by noise. We present some preliminary results over a variation of the dataset of symbols from the GREC 2005 symbol recognition contest.
	Address	La Rochelle; July 2009
	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	GREC
	Notes	DAG			Approved	no
	Call Number	DAG @ dag @ RBO2009			Serial	1444
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	Author	Miquel Ferrer; Ernest Valveny; F. Serratosa; I. Bardaji; Horst Bunke
	Title	Graph-based k-means clustering: A comparison of the set versus the generalized median graph			Type	Conference Article
	Year	2009	Publication	13th International Conference on Computer Analysis of Images and Patterns	Abbreviated Journal
	Volume	5702	Issue		Pages	342–350
	Keywords
	Abstract	In this paper we propose the application of the generalized median graph in a graph-based k-means clustering algorithm. In the graph-based k-means algorithm, the centers of the clusters have been traditionally represented using the set median graph. We propose an approximate method for the generalized median graph computation that allows to use it to represent the centers of the clusters. Experiments on three databases show that using the generalized median graph as the clusters representative yields better results than the set median graph.
	Address	Münster, Germany
	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	978-3-642-03766-5	Medium
	Area		Expedition		Conference	CAIP
	Notes	DAG			Approved	no
	Call Number	DAG @ dag @ FVS2009d			Serial	1219
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	Author	Xavier Baro; Sergio Escalera; Petia Radeva; Jordi Vitria
	Title	Generic Object Recognition in Urban Image Databases			Type	Conference Article
	Year	2009	Publication	12th International Conference of the Catalan Association for Artificial Intelligence	Abbreviated Journal
	Volume	202	Issue		Pages	27-34
	Keywords
	Abstract	In this paper we propose the construction of a visual content layer which describes the visual appearance of geographic locations in a city. We captured, by means of a Mobile Mapping system, a huge set of georeferenced images (>500K) which cover the whole city of Barcelona. For each image, hundreds of region descriptions are computed off-line and described as a hash code. All this information is extracted without an object of reference, which allows to search for any type of objects using their visual appearance. A new Visual Content layer is built over Google Maps, allowing the object recognition information to be organized and fused with other content, like satellite images, street maps, and business locations.
	Address	Cardona (Spain)
	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	978-1-60750-061-2	Medium
	Area		Expedition		Conference	CCIA
	Notes	OR;MILAB;HuPBA;MV			Approved	no
	Call Number	BCNPCL @ bcnpcl @ VER2009			Serial	1183
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	Author	Jordi Gonzalez; Dani Rowe; Javier Varona; Xavier Roca
	Title	Understanding Dynamic Scenes based on Human Sequence Evaluation			Type	Journal Article
	Year	2009	Publication	Image and Vision Computing	Abbreviated Journal	IMAVIS
	Volume	27	Issue	10	Pages	1433–1444
	Keywords	Image Sequence Evaluation; High-level processing of monitored scenes; Segmentation and tracking in complex scenes; Event recognition in dynamic scenes; Human motion understanding; Human behaviour interpretation; Natural-language text generation; Realistic demonstrators
	Abstract	In this paper, a Cognitive Vision System (CVS) is presented, which explains the human behaviour of monitored scenes using natural-language texts. This cognitive analysis of human movements recorded in image sequences is here referred to as Human Sequence Evaluation (HSE) which defines a set of transformation modules involved in the automatic generation of semantic descriptions from pixel values. In essence, the trajectories of human agents are obtained to generate textual interpretations of their motion, and also to infer the conceptual relationships of each agent w.r.t. its environment. For this purpose, a human behaviour model based on Situation Graph Trees (SGTs) is considered, which permits both bottom-up (hypothesis generation) and top-down (hypothesis refinement) analysis of dynamic scenes. The resulting system prototype interprets different kinds of behaviour and reports textual descriptions in multiple languages.
	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	ISE			Approved	no
	Call Number	ISE @ ise @ GRV2009			Serial	1211
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	Author	Ignasi Rius; Jordi Gonzalez; Javier Varona; Xavier Roca
	Title	Action-specific motion prior for efficient bayesian 3D human body tracking			Type	Journal Article
	Year	2009	Publication	Pattern Recognition	Abbreviated Journal	PR
	Volume	42	Issue	11	Pages	2907–2921
	Keywords
	Abstract	In this paper, we aim to reconstruct the 3D motion parameters of a human body model from the known 2D positions of a reduced set of joints in the image plane. Towards this end, an action-speciﬁc motion model is trained from a database of real motion-captured performances. The learnt motion model is used within a particle ﬁltering framework as a priori knowledge on human motion. First, our dynamic model guides the particles according to similar situations previously learnt. Then, the solution space is constrained so only feasible human postures are accepted as valid solutions at each time step. As a result, we are able to track the 3D conﬁguration of the full human body from several cycles of walking motion sequences using only the 2D positions of a very reduced set of joints from lateral or frontal viewpoints.
	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	0031-3203	ISBN		Medium
	Area		Expedition		Conference
	Notes	ISE			Approved	no
	Call Number	ISE @ ise @ RGV2009			Serial	1159
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	Author	Sergio Escalera; Oriol Pujol; Petia Radeva; Jordi Vitria
	Title	Measuring Interest of Human Dyadic Interactions			Type	Conference Article
	Year	2009	Publication	12th International Conference of the Catalan Association for Artificial Intelligence	Abbreviated Journal
	Volume	202	Issue		Pages	45-54
	Keywords
	Abstract	In this paper, we argue that only using behavioural motion information, we are able to predict the interest of observers when looking at face-to-face interactions. We propose a set of movement-related features from body, face, and mouth activity in order to define a set of higher level interaction features, such as stress, activity, speaking engagement, and corporal engagement. Error-Correcting Output Codes framework with an Adaboost base classifier is used to learn to rank the perceived observer's interest in face-to-face interactions. The automatic system shows good correlation between the automatic categorization results and the manual ranking made by the observers. In particular, the learning system shows that stress features have a high predictive power for ranking interest of observers when looking at of face-to-face interactions.
	Address	Cardona (Spain)
	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	978-1-60750-061-2	Medium
	Area		Expedition		Conference	CCIA
	Notes	OR;MILAB;HuPBA;MV			Approved	no
	Call Number	BCNPCL @ bcnpcl @ EPR2009b			Serial	1182
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	Author	Partha Pratim Roy; Umapada Pal; Josep Llados; Mathieu Nicolas Delalandre
	Title	Multi-Oriented and Multi-Sized Touching Character Segmentation using Dynamic Programming			Type	Conference Article
	Year	2009	Publication	10th International Conference on Document Analysis and Recognition	Abbreviated Journal
	Volume		Issue		Pages	11–15
	Keywords
	Abstract	In this paper, we present a scheme towards the segmentation of English multi-oriented touching strings into individual characters. When two or more characters touch, they generate a big cavity region at the background portion. Using Convex Hull information, we use these background information to find some initial points to segment a touching string into possible primitive segments (a primitive segment consists of a single character or a part of a character). Next these primitive segments are merged to get optimum segmentation and dynamic programming is applied using total likelihood of characters as the objective function. SVM classifier is used to find the likelihood of a character. To consider multi-oriented touching strings the features used in the SVM are invariant to character orientation. Circular ring and convex hull ring based approach has been used along with angular information of the contour pixels of the character to make the feature rotation invariant. From the experiment, we obtained encouraging results.
	Address	Barcelona, Spain
	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	978-1-4244-4500-4	Medium
	Area		Expedition		Conference	ICDAR
	Notes	DAG			Approved	no
	Call Number	DAG @ dag @ RPL2009a			Serial	1240
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	Author	Pierluigi Casale; Oriol Pujol; Petia Radeva
	Title	Face-to-face social activity detection using data collected with a wearable device			Type	Conference Article
	Year	2009	Publication	4th Iberian Conference on Pattern Recognition and Image Analysis	Abbreviated Journal
	Volume	5524	Issue		Pages	56–63
	Keywords
	Abstract	In this work the feasibility of building a socially aware badge that learns from user activities is explored. A wearable multisensor device has been prototyped for collecting data about user movements and photos of the environment where the user acts. Using motion data, speaking and other activities have been classified. Images have been analysed in order to complement motion data and help for the detection of social behaviours. A face detector and an activity classifier are both used for detecting if users have a social activity in the time they worn the device. Good results encourage the improvement of the system at both hardware and software level
	Address	Póvoa de Varzim, Portugal
	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	978-3-642-02171-8	Medium
	Area		Expedition		Conference	IbPRIA
	Notes	MILAB;HuPBA			Approved	no
	Call Number	BCNPCL @ bcnpcl @ CPR2009b			Serial	1206
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	Author	Pierluigi Casale; Oriol Pujol; Petia Radeva; Jordi Vitria
	Title	A First Approach to Activity Recognition Using Topic Models			Type	Conference Article
	Year	2009	Publication	12th International Conference of the Catalan Association for Artificial Intelligence	Abbreviated Journal
	Volume	202	Issue		Pages	74 - 82
	Keywords
	Abstract	In this work, we present a first approach to activity patterns discovery by mean of topic models. Using motion data collected with a wearable device we prototype, TheBadge, we analyse raw accelerometer data using Latent Dirichlet Allocation (LDA), a particular instantiation of topic models. Results show that for particular values of the parameters necessary for applying LDA to a countinous dataset, good accuracies in activity classification can be achieved.
	Address	Cardona, Spain
	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	978-1-60750-061-2	Medium
	Area		Expedition		Conference	CCIA
	Notes	OR;MILAB;HuPBA;MV			Approved	no
	Call Number	BCNPCL @ bcnpcl @ CPR2009e			Serial	1231
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	Author	Oscar Camara; Estanislao Oubel; Gemma Piella; Simone Balocco; Mathieu De Craene; Alejandro F. Frangi
	Title	Multi-sequence Registration of Cine, Tagged and Delay-Enhancement MRI with Shift Correction and Steerable Pyramid-Based Detagging			Type	Conference Article
	Year	2009	Publication	5th International Conference on Functional Imaging and Modeling of the Heart	Abbreviated Journal
	Volume	5528	Issue		Pages	330–338
	Keywords
	Abstract	In this work, we present a registration framework for cardiac cine MRI (cMRI), tagged (tMRI) and delay-enhancement MRI (deMRI), where the two main issues to find an accurate alignment between these images have been taking into account: the presence of tags in tMRI and respiration artifacts in all sequences. A steerable pyramid image decomposition has been used for detagging purposes since it is suitable to extract high-order oriented structures by directional adaptive filtering. Shift correction of cMRI is achieved by firstly maximizing the similarity between the Long Axis and Short Axis cMRI. Subsequently, these shift-corrected images are used as target images in a rigid registration procedure with their corresponding tMRI/deMRI in order to correct their shift. The proposed registration framework has been evaluated by 840 registration tests, considerably improving the alignment of the MR images (mean RMS error of 2.04mm vs. 5.44mm).
	Address	Nice, France
	Corporate Author				Thesis
	Publisher	Springer Berlin Heidelberg	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN	0302-9743	ISBN	978-3-642-01931-9	Medium
	Area		Expedition		Conference	FIMH
	Notes	MILAB			Approved	no
	Call Number	BCNPCL @ bcnpcl @ COP2009			Serial	1255
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	Author	Partha Pratim Roy; Umapada Pal; Josep Llados
	Title	Touching Text Character Localization in Graphical Documents using SIFT			Type	Conference Article
	Year	2009	Publication	In proceedings 8th IAPR International Workshop on Graphics Recognition	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract	Interpretation of graphical document images is a challenging task as it requires proper understanding of text/graphics symbols present in such documents. Difficulties arise in graphical document recognition when text and symbol overlapped/touched. Intersection of text and symbols with graphical lines and curves occur frequently in graphical documents and hence separation of such symbols is very difficult. Several pattern recognition and classification techniques exist to recognize isolated text/symbol. But, the touching/overlapping text and symbol recognition has not yet been dealt successfully. An interesting technique, Scale Invariant Feature Transform (SIFT), originally devised for object recognition can take care of overlapping problems. Even if SIFT features have emerged as a very powerful object descriptors, their employment in graphical documents context has not been investigated much. In this paper we present the adaptation of the SIFT approach in the context of text character localization (spotting) in graphical documents. We evaluate the applicability of this technique in such documents and discuss the scope of improvement by combining some state-of-the-art approaches.
	Address	La rochelle; July 2009
	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	GREC
	Notes	DAG			Approved	no
	Call Number	DAG @ dag @ RPL2009c			Serial	1445
Permanent link to this record