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Author David Aldavert; Ricardo Toledo; Arnau Ramisa; Ramon Lopez de Mantaras edit  doi
isbn  openurl
  Title Visual Registration Method For A Low Cost Robot: Computer Vision Systems Type Conference Article
  Year 2009 Publication 7th International Conference on Computer Vision Systems Abbreviated Journal  
  Volume 5815 Issue Pages 204–214  
  Keywords  
  Abstract An autonomous mobile robot must face the correspondence or data association problem in order to carry out tasks like place recognition or unknown environment mapping. In order to put into correspondence two maps, most methods estimate the transformation relating the maps from matches established between low level feature extracted from sensor data. However, finding explicit matches between features is a challenging and computationally expensive task. In this paper, we propose a new method to align obstacle maps without searching explicit matches between features. The maps are obtained from a stereo pair. Then, we use a vocabulary tree approach to identify putative corresponding maps followed by the Newton minimization algorithm to find the transformation that relates both maps. The proposed method is evaluated in a typical office environment showing good performance.  
  Address (up) Belgica  
  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 978-3-642-04666-7 Medium  
  Area Expedition Conference ICVS  
  Notes ADAS Approved no  
  Call Number Admin @ si @ ATR2009b Serial 1247  
Permanent link to this record
 

 
Author Pau Baiget edit  openurl
  Title Modeling Human Behavior for Image Sequence Understanding and Generation Type Book Whole
  Year 2009 Publication PhD Thesis, Universitat Autonoma de Barcelona-CVC Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract The comprehension of animal behavior, especially human behavior, is one of the most ancient and studied problems since the beginning of civilization. The big list of factors that interact to determine a person action require the collaboration of different disciplines, such as psichology, biology, or sociology. In the last years the analysis of human behavior has received great attention also from the computer vision community, given the latest advances in the acquisition of human motion data from image sequences.

Despite the increasing availability of that data, there still exists a gap towards obtaining a conceptual representation of the obtained observations. Human behavior analysis is based on a qualitative interpretation of the results, and therefore the assignment of concepts to quantitative data is linked to a certain ambiguity.

This Thesis tackles the problem of obtaining a proper representation of human behavior in the contexts of computer vision and animation. On the one hand, a good behavior model should permit the recognition and explanation the observed activity in image sequences. On the other hand, such a model must allow the generation of new synthetic instances, which model the behavior of virtual agents.

First, we propose methods to automatically learn the models from observations. Given a set of quantitative results output by a vision system, a normal behavior model is learnt. This results provides a tool to determine the normality or abnormality of future observations. However, machine learning methods are unable to provide a richer description of the observations. We confront this problem by means of a new method that incorporates prior knowledge about the enviornment and about the expected behaviors. This framework, formed by the reasoning engine FMTL and the modeling tool SGT allows the generation of conceptual descriptions of activity in new image sequences. Finally, we demonstrate the suitability of the proposed framework to simulate behavior of virtual agents, which are introduced into real image sequences and interact with observed real agents, thereby easing the generation of augmented reality sequences.

The set of approaches presented in this Thesis has a growing set of potential applications. The analysis and description of behavior in image sequences has its principal application in the domain of smart video--surveillance, in order to detect suspicious or dangerous behaviors. Other applications include automatic sport commentaries, elderly monitoring, road traffic analysis, and the development of semantic video search engines. Alternatively, behavioral virtual agents allow to simulate accurate real situations, such as fires or crowds. Moreover, the inclusion of virtual agents into real image sequences has been widely deployed in the games and cinema industries.
 
  Address (up) Bellaterra (Spain)  
  Corporate Author Thesis Ph.D. thesis  
  Publisher Ediciones Graficas Rey Place of Publication Editor Jordi Gonzalez;Xavier Roca  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number Admin @ si @ Bai2009 Serial 1210  
Permanent link to this record
 

 
Author Mohammad Rouhani; Angel Sappa edit  doi
isbn  openurl
  Title A Novel Approach to Geometric Fitting of Implicit Quadrics Type Conference Article
  Year 2009 Publication 8th International Conference on Advanced Concepts for Intelligent Vision Systems Abbreviated Journal  
  Volume 5807 Issue Pages 121–132  
  Keywords  
  Abstract This paper presents a novel approach for estimating the geometric distance from a given point to the corresponding implicit quadric curve/surface. The proposed estimation is based on the height of a tetrahedron, which is used as a coarse but reliable estimation of the real distance. The estimated distance is then used for finding the best set of quadric parameters, by means of the Levenberg-Marquardt algorithm, which is a common framework in other geometric fitting approaches. Comparisons of the proposed approach with previous ones are provided to show both improvements in CPU time as well as in the accuracy of the obtained results.  
  Address (up) Bordeaux, 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 978-3-642-04696-4 Medium  
  Area Expedition Conference ACIVS  
  Notes ADAS Approved no  
  Call Number ADAS @ adas @ RoS2009 Serial 1194  
Permanent link to this record
 

 
Author Sergio Escalera; Alicia Fornes; Oriol Pujol; Alberto Escudero; Petia Radeva edit  url
isbn  openurl
  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 (up) Cairo, Egypt  
  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 978-1-4244-5653-6 Medium  
  Area Expedition Conference ICIP  
  Notes MILAB;HuPBA;DAG Approved no  
  Call Number BCNPCL @ bcnpcl @ EFP2009b Serial 1184  
Permanent link to this record
 

 
Author Jose Manuel Alvarez; Ferran Diego; Joan Serrat; Antonio Lopez edit   pdf
doi  isbn
openurl 
  Title Automatic Ground-truthing using video registration for on-board detection algorithms Type Conference Article
  Year 2009 Publication 16th IEEE International Conference on Image Processing Abbreviated Journal  
  Volume Issue Pages 4389 - 4392  
  Keywords  
  Abstract Ground-truth data is essential for the objective evaluation of object detection methods in computer vision. Many works claim their method is robust but they support it with experiments which are not quantitatively assessed with regard some ground-truth. This is one of the main obstacles to properly evaluate and compare such methods. One of the main reasons is that creating an extensive and representative ground-truth is very time consuming, specially in the case of video sequences, where thousands of frames have to be labelled. Could such a ground-truth be generated, at least in part, automatically? Though it may seem a contradictory question, we show that this is possible for the case of video sequences recorded from a moving camera. The key idea is transferring existing frame segmentations from a reference sequence into another video sequence recorded at a different time on the same track, possibly under a different ambient lighting. We have carried out experiments on several video sequence pairs and quantitatively assessed the precision of the transformed ground-truth, which prove that our approach is not only feasible but also quite accurate.  
  Address (up) Cairo, Egypt  
  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 1522-4880 ISBN 978-1-4244-5653-6 Medium  
  Area Expedition Conference ICIP  
  Notes ADAS Approved no  
  Call Number ADAS @ adas @ ADS2009 Serial 1201  
Permanent link to this record
 

 
Author Angel Sappa; Mohammad Rouhani edit  doi
isbn  openurl
  Title Efficient Distance Estimation for Fitting Implicit Quadric Surfaces Type Conference Article
  Year 2009 Publication 16th IEEE International Conference on Image Processing Abbreviated Journal  
  Volume Issue Pages 3521–3524  
  Keywords  
  Abstract This paper presents a novel approach for estimating the shortest Euclidean distance from a given point to the corresponding implicit quadric fitting surface. It first estimates the orthogonal orientation to the surface from the given point; then the shortest distance is directly estimated by intersecting the implicit surface with a line passing through the given point according to the estimated orthogonal orientation. The proposed orthogonal distance estimation is easily obtained without increasing computational complexity; hence it can be used in error minimization surface fitting frameworks. Comparisons of the proposed metric with previous approaches are provided to show both improvements in CPU time as well as in the accuracy of the obtained results. Surfaces fitted by using the proposed geometric distance estimation and state of the art metrics are presented to show the viability of the proposed approach.  
  Address (up) Cairo, Egypt  
  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 1522-4880 ISBN 978-1-4244-5653-6 Medium  
  Area Expedition Conference ICIP  
  Notes ADAS Approved no  
  Call Number ADAS @ adas @ SaR2009 Serial 1232  
Permanent link to this record
 

 
Author Carlo Gatta; Petia Radeva edit  doi
isbn  openurl
  Title Bilateral Enhancers Type Conference Article
  Year 2009 Publication 16th IEEE International Conference on Image Processing Abbreviated Journal  
  Volume Issue Pages 3161-3165  
  Keywords  
  Abstract Ten years ago the concept of bilateral filtering (BF) became popular in the image processing community. The core of the idea is to blend the effect of a spatial filter, as e.g. the Gaussian filter, with the effect of a filter that acts on image values. The two filters acts on orthogonal domains of a picture: the 2D lattice of the image support and the intensity (or color) domain. The BF approach is an intuitive way to blend these two filters giving rise to algorithms that perform difficult tasks requiring a relatively simple design. In this paper we extend the concept of BF, proposing the bilateral enhancers (BE). We show how to design proper functions to obtain an edge-preserving smoothing and a selective sharpening. Moreover, we show that the proposed algorithm can perform edge-preserving smoothing and selective sharpening simultaneously in a single filtering.  
  Address (up) Cairo, Egypt  
  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 1522-4880 ISBN 978-1-4244-5653-6 Medium  
  Area Expedition Conference ICIP  
  Notes MILAB Approved no  
  Call Number BCNPCL @ bcnpcl @ GaR2009b Serial 1243  
Permanent link to this record
 

 
Author Sergio Escalera; Xavier Baro; Jordi Vitria; Petia Radeva edit  doi
isbn  openurl
  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 (up) 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 @ EBV2009 Serial 1181  
Permanent link to this record
 

 
Author Sergio Escalera; Oriol Pujol; Petia Radeva; Jordi Vitria edit  doi
isbn  openurl
  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 (up) 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  
Permanent link to this record
 

 
Author Xavier Baro; Sergio Escalera; Petia Radeva; Jordi Vitria edit  doi
isbn  openurl
  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 (up) 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 Francesco Ciompi; Oriol Pujol; Oriol Rodriguez-Leor; Angel Serrano; J. Mauri; Petia Radeva edit  doi
isbn  openurl
  Title On in-vitro and in-vivo IVUS data fusion Type Conference Article
  Year 2009 Publication 12th International Conference of the Catalan Association for Artificial Intelligence Abbreviated Journal  
  Volume 202 Issue Pages 147-156  
  Keywords  
  Abstract The design and the validation of an automatic plaque characterization technique based on Intravascular Ultrasound (IVUS) usually requires a data ground-truth. The histological analysis of post-mortem coronary arteries is commonly assumed as the state-of-the-art process for the extraction of a reliable data-set of atherosclerotic plaques. Unfortunately, the amount of data provided by this technique is usually few, due to the difficulties in collecting post-mortem cases and phenomena of tissue spoiling during histological analysis. In this paper we tackle the process of fusing in-vivo and in-vitro IVUS data starting with the analysis of recently proposed approaches for the creation of an enhanced IVUS data-set; furthermore, we propose a new approach, named pLDS, based on semi-supervised learning with a data selection criterion. The enhanced data-set obtained by each one of the analyzed approaches is used to train a classifier for tissue characterization purposes. Finally, the discriminative power of each classifier is quantitatively assessed and compared by classifying a data-set of validated in-vitro IVUS data.  
  Address (up) 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 MILAB;HuPBA Approved no  
  Call Number BCNPCL @ bcnpcl @ CPR2009d Serial 1204  
Permanent link to this record
 

 
Author Pierluigi Casale; Oriol Pujol; Petia Radeva; Jordi Vitria edit  doi
isbn  openurl
  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 (up) 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  
Permanent link to this record
 

 
Author Arnau Ramisa; Shrihari Vasudevan; David Aldavert; Ricardo Toledo; Ramon Lopez de Mantaras edit  url
doi  isbn
openurl 
  Title Evaluation of the SIFT Object Recognition Method in Mobile Robots: Frontiers in Artificial Intelligence and Applications Type Conference Article
  Year 2009 Publication 12th International Conference of the Catalan Association for Artificial Intelligence Abbreviated Journal  
  Volume 202 Issue Pages 9-18  
  Keywords  
  Abstract General object recognition in mobile robots is of primary importance in order to enhance the representation of the environment that robots will use for their reasoning processes. Therefore, we contribute reduce this gap by evaluating the SIFT Object Recognition method in a challenging dataset, focusing on issues relevant to mobile robotics. Resistance of the method to the robotics working conditions was found, but it was limited mainly to well-textured objects.  
  Address (up) 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 0922-6389 ISBN 978-1-60750-061-2 Medium  
  Area Expedition Conference CCIA  
  Notes ADAS Approved no  
  Call Number Admin @ si @ RVA2009 Serial 1248  
Permanent link to this record
 

 
Author Nicola Bellotto; Eric Sommerlade; Ben Benfold; Charles Bibby; I. Reid; Daniel Roth; Luc Van Gool; Carles Fernandez; Jordi Gonzalez edit   pdf
doi  openurl
  Title A Distributed Camera System for Multi-Resolution Surveillance Type Conference Article
  Year 2009 Publication 3rd ACM/IEEE International Conference on Distributed Smart Cameras Abbreviated Journal  
  Volume Issue Pages  
  Keywords 10.1109/ICDSC.2009.5289413  
  Abstract We describe an architecture for a multi-camera, multi-resolution surveillance system. The aim is to support a set of distributed static and pan-tilt-zoom (PTZ) cameras and visual tracking algorithms, together with a central supervisor unit. Each camera (and possibly pan-tilt device) has a dedicated process and processor. Asynchronous interprocess communications and archiving of data are achieved in a simple and effective way via a central repository, implemented using an SQL database. Visual tracking data from static views are stored dynamically into tables in the database via client calls to the SQL server. A supervisor process running on the SQL server determines if active zoom cameras should be dispatched to observe a particular target, and this message is effected via writing demands into another database table. We show results from a real implementation of the system comprising one static camera overviewing the environment under consideration and a PTZ camera operating under closed-loop velocity control, which uses a fast and robust level-set-based region tracker. Experiments demonstrate the effectiveness of our approach and its feasibility to multi-camera systems for intelligent surveillance.  
  Address (up) Como, Italy  
  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 ICDSC  
  Notes Approved no  
  Call Number ISE @ ise @ BSB2009 Serial 1205  
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Author Xavier Boix; Josep M. Gonfaus; Fahad Shahbaz Khan; Joost Van de Weijer; Andrew Bagdanov; Marco Pedersoli; Jordi Gonzalez; Joan Serrat edit  openurl
  Title Combining local and global bag-of-word representations for semantic segmentation Type Conference Article
  Year 2009 Publication Workshop on The PASCAL Visual Object Classes Challenge Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address (up) Kyoto (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 ISBN Medium  
  Area Expedition Conference ICCV  
  Notes ADAS;ISE Approved no  
  Call Number ADAS @ adas @ BGS2009 Serial 1273  
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