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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 (up)
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes ISE Approved no
Call Number ISE @ ise @ BFR2009 Serial 1170
Permanent link to this record
 
 
Author Javier Vazquez; C. Alejandro Parraga; Maria Vanrell; Ramon Baldrich
Title Color Constancy Algorithms: Psychophysical Evaluation on a New Dataset Type Journal Article
Year 2009 Publication Journal of Imaging Science and Technology Abbreviated Journal
Volume 53 Issue 3 Pages 031105–9
Keywords
Abstract The estimation of the illuminant of a scene from a digital image has been the goal of a large amount of research in computer vision. Color constancy algorithms have dealt with this problem by defining different heuristics to select a unique solution from within the feasible set. The performance of these algorithms has shown that there is still a long way to go to globally solve this problem as a preliminary step in computer vision. In general, performance evaluation has been done by comparing the angular error between the estimated chromaticity and the chromaticity of a canonical illuminant, which is highly dependent on the image dataset. Recently, some workers have used high-level constraints to estimate illuminants; in this case selection is based on increasing the performance on the subsequent steps of the systems. In this paper we propose a new performance measure, the perceptual angular error. It evaluates the performance of a color constancy algorithm according to the perceptual preferences of humans, or naturalness (instead of the actual optimal solution) and is independent of the visual task. We show the results of a new psychophysical experiment comparing solutions from three different color constancy algorithms. Our results show that in more than a half of the judgments the preferred solution is not the one closest to the optimal solution. Our experiments were performed on a new dataset of images acquired with a calibrated camera with an attached neutral grey sphere, which better copes with the illuminant variations of the scene.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title (up)
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes CIC Approved no
Call Number CAT @ cat @ VPV2009a Serial 1171
Permanent link to this record
 
 
Author Antonio Clavelli; Dimosthenis Karatzas
Title Text Segmentation in Colour Posters from the Spanish Civil War Era Type Conference Article
Year 2009 Publication 10th International Conference on Document Analysis and Recognition Abbreviated Journal
Volume Issue Pages 181 - 185
Keywords
Abstract The extraction of textual content from colour documents of a graphical nature is a complicated task. The text can be rendered in any colour, size and orientation while the existence of complex background graphics with repetitive patterns can make its localization and segmentation extremely difficult.
Here, we propose a new method for extracting textual content from such colour images that makes no assumption as to the size of the characters, their orientation or colour, while it is tolerant to characters that do not follow a straight baseline. We evaluate this method on a collection of documents with historical
connotations: the Posters from the Spanish Civil War.
Address Barcelona, Spain
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title (up)
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 @ ClK2009 Serial 1172
Permanent link to this record
 
 
Author Albert Gordo; Ernest Valveny
Title A rotation invariant page layout descriptor for document classification and retrieval Type Conference Article
Year 2009 Publication 10th International Conference on Document Analysis and Recognition Abbreviated Journal
Volume Issue Pages 481–485
Keywords
Abstract Document classification usually requires of structural features such as the physical layout to obtain good accuracy rates on complex documents. This paper introduces a descriptor of the layout and a distance measure based on the cyclic dynamic time warping which can be computed in O(n2). This descriptor is translation invariant and can be easily modified to be scale and rotation invariant. Experiments with this descriptor and its rotation invariant modification are performed on the Girona archives database and compared against another common layout distance, the minimum weight edge cover. The experiments show that these methods outperform the MWEC both in accuracy and speed, particularly on rotated documents.
Address Barcelona, Spain
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title (up)
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 @ GoV2009a Serial 1175
Permanent link to this record
 
 
Author Marçal Rusiñol; Agnes Borras; Josep Llados
Title Relational Indexing of Vectorial Primitives for Symbol Spotting in Line-Drawing Images Type Journal Article
Year 2010 Publication Pattern Recognition Letters Abbreviated Journal PRL
Volume 31 Issue 3 Pages 188–201
Keywords Document image analysis and recognition, Graphics recognition, Symbol spotting ,Vectorial representations, Line-drawings
Abstract This paper presents a symbol spotting approach for indexing by content a database of line-drawing images. As line-drawings are digital-born documents designed by vectorial softwares, instead of using a pixel-based approach, we present a spotting method based on vector primitives. Graphical symbols are represented by a set of vectorial primitives which are described by an off-the-shelf shape descriptor. A relational indexing strategy aims to retrieve symbol locations into the target documents by using a combined numerical-relational description of 2D structures. The zones which are likely to contain the queried symbol are validated by a Hough-like voting scheme. In addition, a performance evaluation framework for symbol spotting in graphical documents is proposed. The presented methodology has been evaluated with a benchmarking set of architectural documents achieving good performance results.
Address
Corporate Author Thesis
Publisher Elsevier Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title (up)
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes DAG Approved no
Call Number DAG @ dag @ RBL2010 Serial 1177
Permanent link to this record
 
 
Author Marçal Rusiñol; Josep Llados
Title Logo Spotting by a Bag-of-words Approach for Document Categorization Type Conference Article
Year 2009 Publication 10th International Conference on Document Analysis and Recognition Abbreviated Journal
Volume Issue Pages 111–115
Keywords
Abstract In this paper we present a method for document categorization which processes incoming document images such as invoices or receipts. The categorization of these document images is done in terms of the presence of a certain graphical logo detected without segmentation. The graphical logos are described by a set of local features and the categorization of the documents is performed by the use of a bag-of-words model. Spatial coherence rules are added to reinforce the correct category hypothesis, aiming also to spot the logo inside the document image. Experiments which demonstrate the effectiveness of this system on a large set of real data are presented.
Address Barcelona; Spain
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title (up)
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 @ RuL2009b Serial 1179
Permanent link to this record
 
 
Author Sergio Escalera; Alicia Fornes; O. Pujol; Petia Radeva; Gemma Sanchez; Josep Llados
Title Blurred Shape Model for Binary and Grey-level Symbol Recognition Type Journal Article
Year 2009 Publication Pattern Recognition Letters Abbreviated Journal PRL
Volume 30 Issue 15 Pages 1424–1433
Keywords
Abstract Many symbol recognition problems require the use of robust descriptors in order to obtain rich information of the data. However, the research of a good descriptor is still an open issue due to the high variability of symbols appearance. Rotation, partial occlusions, elastic deformations, intra-class and inter-class variations, or high variability among symbols due to different writing styles, are just a few problems. In this paper, we introduce a symbol shape description to deal with the changes in appearance that these types of symbols suffer. The shape of the symbol is aligned based on principal components to make the recognition invariant to rotation and reflection. Then, we present the Blurred Shape Model descriptor (BSM), where new features encode the probability of appearance of each pixel that outlines the symbols shape. Moreover, we include the new descriptor in a system to deal with multi-class symbol categorization problems. Adaboost is used to train the binary classifiers, learning the BSM features that better split symbol classes. Then, the binary problems are embedded in an Error-Correcting Output Codes framework (ECOC) to deal with the multi-class case. The methodology is evaluated on different synthetic and real data sets. State-of-the-art descriptors and classifiers are compared, showing the robustness and better performance of the present scheme to classify symbols with high variability of appearance.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title (up)
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes HuPBA; DAG; MILAB Approved no
Call Number BCNPCL @ bcnpcl @ EFP2009a Serial 1180
Permanent link to this record
 
 
Author Sergio Escalera; Xavier Baro; Jordi Vitria; Petia Radeva
Title Text Detection in Urban Scenes (video sample) Type Conference Article
Year 2009 Publication 12th International Conference of the Catalan Association for Artificial Intelligence Abbreviated Journal
Volume 202 Issue Pages 35–44
Keywords
Abstract Abstract. Text detection in urban scenes is a hard task due to the high variability of text appearance: different text fonts, changes in the point of view, or partial occlusion are just a few problems. Text detection can be specially suited for georeferencing business, navigation, tourist assistance, or to help visual impaired people. In this paper, we propose a general methodology to deal with the problem of text detection in outdoor scenes. The method is based on learning spatial information of gradient based features and Census Transform images using a cascade of classifiers. The method is applied in the context of Mobile Mapping systems, where a mobile vehicle captures urban image sequences. Moreover, a cover data set is presented and tested with the new methodology. The results show high accuracy when detecting multi-linear text regions with high variability of appearance, at same time that it preserves a low false alarm rate compared to classical approaches
Address Cardona (Spain)
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title (up)
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 @ EBV2009 Serial 1181
Permanent link to this record
 
 
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 (up)
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
Permanent link to this record
 
 
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 (up)
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
Permanent link to this record
 
 
Author Sergio Escalera; Alicia Fornes; Oriol Pujol; Alberto Escudero; Petia Radeva
Title Circular Blurred Shape Model for Symbol Spotting in Documents Type Conference Article
Year 2009 Publication 16th IEEE International Conference on Image Processing Abbreviated Journal
Volume Issue Pages 1985-1988
Keywords
Abstract Symbol spotting problem requires feature extraction strategies able to generalize from training samples and to localize the target object while discarding most part of the image. In the case of document analysis, symbol spotting techniques have to deal with a high variability of symbols' appearance. In this paper, we propose the Circular Blurred Shape Model descriptor. Feature extraction is performed capturing the spatial arrangement of significant object characteristics in a correlogram structure. Shape information from objects is shared among correlogram regions, being tolerant to the irregular deformations. Descriptors are learnt using a cascade of classifiers and Abadoost as the base classifier. Finally, symbol spotting is performed by means of a windowing strategy using the learnt cascade over plan and old musical score documents. Spotting and multi-class categorization results show better performance comparing with the state-of-the-art descriptors.
Address Cairo, Egypt
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title (up)
Series Volume Series Issue Edition
ISSN ISBN 978-1-4244-5653-6 Medium
Area Expedition Conference ICIP
Notes MILAB;HuPBA;DAG Approved no
Call Number BCNPCL @ bcnpcl @ EFP2009b Serial 1184
Permanent link to this record
 
 
Author Sergio Escalera; Eloi Puertas; Petia Radeva; Oriol Pujol
Title Multimodal laughter recognition in video conversations Type Conference Article
Year 2009 Publication 2nd IEEE Workshop on CVPR for Human communicative Behavior analysis Abbreviated Journal
Volume Issue Pages 110–115
Keywords
Abstract Laughter detection is an important area of interest in the Affective Computing and Human-computer Interaction fields. In this paper, we propose a multi-modal methodology based on the fusion of audio and visual cues to deal with the laughter recognition problem in face-to-face conversations. The audio features are extracted from the spectogram and the video features are obtained estimating the mouth movement degree and using a smile and laughter classifier. Finally, the multi-modal cues are included in a sequential classifier. Results over videos from the public discussion blog of the New York Times show that both types of features perform better when considered together by the classifier. Moreover, the sequential methodology shows to significantly outperform the results obtained by an Adaboost classifier.
Address Miami (USA)
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title (up)
Series Volume Series Issue Edition
ISSN 2160-7508 ISBN 978-1-4244-3994-2 Medium
Area Expedition Conference CVPR
Notes MILAB;HuPBA Approved no
Call Number BCNPCL @ bcnpcl @ EPR2009c Serial 1188
Permanent link to this record
 
 
Author Xavier Baro; Sergio Escalera; Petia Radeva; Jordi Vitria
Title Visual Content Layer for Scalable Recognition in Urban Image Databases, Internet Multimedia Search and Mining Type Conference Article
Year 2009 Publication 10th IEEE International Conference on Multimedia and Expo Abbreviated Journal
Volume Issue Pages 1616–1619
Keywords
Abstract Rich online map interaction represents a useful tool to get multimedia information related to physical places. With this type of systems, users can automatically compute the optimal route for a trip or to look for entertainment places or hotels near their actual position. Standard maps are defined as a fusion of layers, where each one contains specific data such height, streets, or a particular business location. 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. This allows an efficient and scalable way of accessing maps by visual content.
Address New York (USA)
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title (up)
Series Volume Series Issue Edition
ISSN ISBN 978-1-4244-4291-1 Medium
Area Expedition Conference ICME
Notes OR;MILAB;HuPBA;MV Approved no
Call Number BCNPCL @ bcnpcl @ BER2009 Serial 1189
Permanent link to this record
 
 
Author Sergio Escalera; Oriol Pujol; Petia Radeva
Title Recoding Error-Correcting Output Codes Type Conference Article
Year 2009 Publication 8th International Workshop of Multiple Classifier Systems Abbreviated Journal
Volume 5519 Issue Pages 11–21
Keywords
Abstract One of the most widely applied techniques to deal with multi- class categorization problems is the pairwise voting procedure. Recently, this classical approach has been embedded in the Error-Correcting Output Codes framework (ECOC). This framework is based on a coding step, where a set of binary problems are learnt and coded in a matrix, and a decoding step, where a new sample is tested and classified according to a comparison with the positions of the coded matrix. In this paper, we present a novel approach to redefine without retraining, in a problem-dependent way, the one-versus-one coding matrix so that the new coded information increases the generalization capability of the system. Moreover, the final classification can be tuned with the inclusion of a weighting matrix in the decoding step. The approach has been validated over several UCI Machine Learning repository data sets and two real multi-class problems: traffic sign and face categorization. The results show that performance improvements are obtained when comparing the new approach to one of the best ECOC designs (one-versus-one). Furthermore, the novel methodology obtains at least the same performance than the one-versus-one ECOC design.
Address Reykjavik (Iceland)
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title (up)
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-02325-5 Medium
Area Expedition Conference MCS
Notes MILAB;HuPBA Approved no
Call Number BCNPCL @ bcnpcl @ EPR2009d Serial 1190
Permanent link to this record
 
 
Author Javier Vazquez; C. Alejandro Parraga; Maria Vanrell
Title Ordinal pairwise method for natural images comparison Type Journal Article
Year 2009 Publication Perception Abbreviated Journal PER
Volume 38 Issue Pages 180
Keywords
Abstract 38(Suppl.)ECVP Abstract Supplement
We developed a new psychophysical method to compare different colour appearance models when applied to natural scenes. The method was as follows: two images (processed by different algorithms) were displayed on a CRT monitor and observers were asked to select the most natural of them. The original images were gathered by means of a calibrated trichromatic digital camera and presented one on top of the other on a calibrated screen. The selection was made by pressing on a 6-button IR box, which allowed observers to consider not only the most natural but to rate their selection. The rating system allowed observers to register how much more natural was their chosen image (eg, much more, definitely more, slightly more), which gave us valuable extra information on the selection process. The results were analysed considering both the selection as a binary choice (using Thurstone's law of comparative judgement) and using Bradley-Terry method for ordinal comparison. Our results show a significant difference in the rating scales obtained. Although this method has been used in colour constancy algorithm comparisons, its uses are much wider, eg to compare algorithms of image compression, rendering, recolouring, etc.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title (up)
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes CIC Approved no
Call Number CAT @ cat @ VPV2009b Serial 1191
Permanent link to this record