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Author Diego Alejandro Cheda; Daniel Ponsa; Antonio Lopez
Title Camera Egomotion Estimation in the ADAS Context Type Conference Article
Year 2010 Publication 13th International IEEE Annual Conference on Intelligent Transportation Systems Abbreviated Journal
Volume Issue Pages 1415–1420
Keywords
Abstract Camera-based Advanced Driver Assistance Systems (ADAS) have concentrated many research efforts in the last decades. Proposals based on monocular cameras require the knowledge of the camera pose with respect to the environment, in order to reach an efficient and robust performance. A common assumption in such systems is considering the road as planar, and the camera pose with respect to it as approximately known. However, in real situations, the camera pose varies along time due to the vehicle movement, the road slope, and irregularities on the road surface. Thus, the changes in the camera position and orientation (i.e., the egomotion) are critical information that must be estimated at every frame to avoid poor performances. This work focuses on egomotion estimation from a monocular camera under the ADAS context. We review and compare egomotion methods with simulated and real ADAS-like sequences. Basing on the results of our experiments, we show which of the considered nonlinear and linear algorithms have the best performance in this domain.
Address Madeira Island (Portugal)
Corporate Author Thesis
Publisher (up) Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2153-0009 ISBN 978-1-4244-7657-2 Medium
Area Expedition Conference ITSC
Notes ADAS Approved no
Call Number ADAS @ adas @ CPL2010 Serial 1425
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Author Susana Alvarez; Anna Salvatella; Maria Vanrell; Xavier Otazu
Title Perceptual color texture codebooks for retrieving in highly diverse texture datasets Type Conference Article
Year 2010 Publication 20th International Conference on Pattern Recognition Abbreviated Journal
Volume Issue Pages 866–869
Keywords
Abstract Color and texture are visual cues of different nature, their integration in a useful visual descriptor is not an obvious step. One way to combine both features is to compute texture descriptors independently on each color channel. A second way is integrate the features at a descriptor level, in this case arises the problem of normalizing both cues. A significant progress in the last years in object recognition has provided the bag-of-words framework that again deals with the problem of feature combination through the definition of vocabularies of visual words. Inspired in this framework, here we present perceptual textons that will allow to fuse color and texture at the level of p-blobs, which is our feature detection step. Feature representation is based on two uniform spaces representing the attributes of the p-blobs. The low-dimensionality of these text on spaces will allow to bypass the usual problems of previous approaches. Firstly, no need for normalization between cues; and secondly, vocabularies are directly obtained from the perceptual properties of text on spaces without any learning step. Our proposal improve current state-of-art of color-texture descriptors in an image retrieval experiment over a highly diverse texture dataset from Corel.
Address Istanbul (Turkey)
Corporate Author Thesis
Publisher (up) 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 978-1-4244-7542-1 Medium
Area Expedition Conference ICPR
Notes CIC Approved no
Call Number CAT @ cat @ ASV2010b Serial 1426
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Author Sergio Escalera; Petia Radeva; Jordi Vitria; Xavier Baro; Bogdan Raducanu
Title Modelling and Analyzing Multimodal Dyadic Interactions Using Social Networks Type Conference Article
Year 2010 Publication 12th International Conference on Multimodal Interfaces and 7th Workshop on Machine Learning for Multimodal Interaction. Abbreviated Journal
Volume Issue Pages
Keywords Social interaction; Multimodal fusion, Influence model; Social network analysis
Abstract Social network analysis became a common technique used to model and quantify the properties of social interactions. In this paper, we propose an integrated framework to explore the characteristics of a social network extracted from
multimodal dyadic interactions. First, speech detection is performed through an audio/visual fusion scheme based on stacked sequential learning. In the audio domain, speech is detected through clusterization of audio features. Clusters
are modelled by means of an One-state Hidden Markov Model containing a diagonal covariance Gaussian Mixture Model. In the visual domain, speech detection is performed through differential-based feature extraction from the segmented
mouth region, and a dynamic programming matching procedure. Second, in order to model the dyadic interactions, we employed the Influence Model whose states
encode the previous integrated audio/visual data. Third, the social network is extracted based on the estimated influences. For our study, we used a set of videos belonging to New York Times’ Blogging Heads opinion blog. The results
are reported both in terms of accuracy of the audio/visual data fusion and centrality measures used to characterize the social network.
Address Beijing (China)
Corporate Author Thesis
Publisher (up) 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 ICMI-MLI
Notes OR;MILAB;HUPBA;MV Approved no
Call Number BCNPCL @ bcnpcl @ ERV2010 Serial 1427
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Author Jose Manuel Alvarez; Felipe Lumbreras; Theo Gevers; Antonio Lopez
Title Geographic Information for vision-based Road Detection Type Conference Article
Year 2010 Publication IEEE Intelligent Vehicles Symposium Abbreviated Journal
Volume Issue Pages 621–626
Keywords road detection
Abstract Road detection is a vital task for the development of autonomous vehicles. The knowledge of the free road surface ahead of the target vehicle can be used for autonomous driving, road departure warning, as well as to support advanced driver assistance systems like vehicle or pedestrian detection. Using vision to detect the road has several advantages in front of other sensors: richness of features, easy integration, low cost or low power consumption. Common vision-based road detection approaches use low-level features (such as color or texture) as visual cues to group pixels exhibiting similar properties. However, it is difficult to foresee a perfect clustering algorithm since roads are in outdoor scenarios being imaged from a mobile platform. In this paper, we propose a novel high-level approach to vision-based road detection based on geographical information. The key idea of the algorithm is exploiting geographical information to provide a rough detection of the road. Then, this segmentation is refined at low-level using color information to provide the final result. The results presented show the validity of our approach.
Address San Diego; CA; USA
Corporate Author Thesis
Publisher (up) 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 IV
Notes ADAS;ISE Approved no
Call Number ADAS @ adas @ ALG2010 Serial 1428
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Author Jaume Amores; David Geronimo; Antonio Lopez
Title Multiple instance and active learning for weakly-supervised object-class segmentation Type Conference Article
Year 2010 Publication 3rd IEEE International Conference on Machine Vision Abbreviated Journal
Volume Issue Pages
Keywords Multiple Instance Learning; Active Learning; Object-class segmentation.
Abstract In object-class segmentation, one of the most tedious tasks is to manually segment many object examples in order to learn a model of the object category. Yet, there has been little research on reducing the degree of manual annotation for
object-class segmentation. In this work we explore alternative strategies which do not require full manual segmentation of the object in the training set. In particular, we study the use of bounding boxes as a coarser and much cheaper form of segmentation and we perform a comparative study of several Multiple-Instance Learning techniques that allow to obtain a model with this type of weak annotation. We show that some of these methods can be competitive, when used with coarse
segmentations, with methods that require full manual segmentation of the objects. Furthermore, we show how to use active learning combined with this weakly supervised strategy.
As we see, this strategy permits to reduce the amount of annotation and optimize the number of examples that require full manual segmentation in the training set.
Address Hong-Kong
Corporate Author Thesis
Publisher (up) 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 ICMV
Notes ADAS Approved no
Call Number ADAS @ adas @ AGL2010b Serial 1429
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Author Joan Serrat; Antonio Lopez
Title Deteccion automatica de lineas de carril para la asistencia a la conduccion Type Miscellaneous
Year 2010 Publication UAB Divulga – Revista de divulgacion cientifica Abbreviated Journal
Volume Issue Pages
Keywords
Abstract La detección por cámara de las líneas de carril en las carreteras puede ser una solución asequible a los riesgos de conducción generados por los adelantamientos o las salidas de carril. Este trabajo propone un sistema que funciona en tiempo real y que obtiene muy buenos resultados. El sistema está preparado para identificar las líneas en condiciones de visibilidad poco favorables, como puede ser la conducción nocturna o con otros vehículos que dificulten la visión.
Address Bellaterra (Spain)
Corporate Author Thesis
Publisher (up) Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes ADAS Approved no
Call Number ADAS @ adas @ SeL2010 Serial 1430
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Author Albert Gordo; Jaume Gibert; Ernest Valveny; Marçal Rusiñol
Title A Kernel-based Approach to Document Retrieval Type Conference Article
Year 2010 Publication 9th IAPR International Workshop on Document Analysis Systems Abbreviated Journal
Volume Issue Pages 377–384
Keywords
Abstract In this paper we tackle the problem of document image retrieval by combining a similarity measure between documents and the probability that a given document belongs to a certain class. The membership probability to a specific class is computed using Support Vector Machines in conjunction with similarity measure based kernel applied to structural document representations. In the presented experiments, we use different document representations, both visual and structural, and we apply them to a database of historical documents. We show how our method based on similarity kernels outperforms the usual distance-based retrieval.
Address Boston; USA;
Corporate Author Thesis
Publisher (up) Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 978-1-60558-773-8 Medium
Area Expedition Conference DAS
Notes DAG Approved no
Call Number DAG @ dag @ GGV2010 Serial 1431
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Author Antonio Clavelli; Dimosthenis Karatzas; Josep Llados
Title A framework for the assessment of text extraction algorithms on complex colour images Type Conference Article
Year 2010 Publication 9th IAPR International Workshop on Document Analysis Systems Abbreviated Journal
Volume Issue Pages 19–26
Keywords
Abstract The availability of open, ground-truthed datasets and clear performance metrics is a crucial factor in the development of an application domain. The domain of colour text image analysis (real scenes, Web and spam images, scanned colour documents) has traditionally suffered from a lack of a comprehensive performance evaluation framework. Such a framework is extremely difficult to specify, and corresponding pixel-level accurate information tedious to define. In this paper we discuss the challenges and technical issues associated with developing such a framework. Then, we describe a complete framework for the evaluation of text extraction methods at multiple levels, provide a detailed ground-truth specification and present a case study on how this framework can be used in a real-life situation.
Address Boston; USA;
Corporate Author Thesis
Publisher (up) Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 978-1-60558-773-8 Medium
Area Expedition Conference DAS
Notes DAG Approved no
Call Number DAG @ dag @ CKL2010 Serial 1432
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Author Partha Pratim Roy; Umapada Pal; Josep Llados
Title Query Driven Word Retrieval in Graphical Documents Type Conference Article
Year 2010 Publication 9th IAPR International Workshop on Document Analysis Systems Abbreviated Journal
Volume Issue Pages 191–198
Keywords
Abstract In this paper, we present an approach towards the retrieval of words from graphical document images. In graphical documents, due to presence of multi-oriented characters in non-structured layout, word indexing is a challenging task. The proposed approach uses recognition results of individual components to form character pairs with the neighboring components. An indexing scheme is designed to store the spatial description of components and to access them efficiently. Given a query text word (ascii/unicode format), the character pairs present in it are searched in the document. Next the retrieved character pairs are linked sequentially to form character string. Dynamic programming is applied to find different instances of query words. A string edit distance is used here to match the query word as the objective function. Recognition of multi-scale and multi-oriented character component is done using Support Vector Machine classifier. To consider multi-oriented character strings the features used in the SVM are invariant to character orientation. Experimental results show that the method is efficient to locate a query word from multi-oriented text in graphical documents.
Address Boston; USA
Corporate Author Thesis
Publisher (up) Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 978-1-60558-773-8 Medium
Area Expedition Conference DAS
Notes DAG Approved no
Call Number DAG @ dag @ RPL2010b Serial 1433
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Author Marçal Rusiñol; Josep Llados
Title Efficient Logo Retrieval Through Hashing Shape Context Descriptors Type Conference Article
Year 2010 Publication 9th IAPR International Workshop on Document Analysis Systems Abbreviated Journal
Volume Issue Pages 215–222
Keywords
Abstract In this paper, we present an approach towards the retrieval of words from graphical document images. In graphical documents, due to presence of multi-oriented characters in non-structured layout, word indexing is a challenging task. The proposed approach uses recognition results of individual components to form character pairs with the neighboring components. An indexing scheme is designed to store the spatial description of components and to access them efficiently. Given a query text word (ascii/unicode format), the character pairs present in it are searched in the document. Next the retrieved character pairs are linked sequentially to form character string. Dynamic programming is applied to find different instances of query words. A string edit distance is used here to match the query word as the objective function. Recognition of multi-scale and multi-oriented character component is done using Support Vector Machine classifier. To consider multi-oriented character strings the features used in the SVM are invariant to character orientation. Experimental results show that the method is efficient to locate a query word from multi-oriented text in graphical documents.
Address Boston; USA
Corporate Author Thesis
Publisher (up) 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 DAS
Notes DAG Approved no
Call Number DAG @ dag @ RuL2010b Serial 1434
Permanent link to this record
 

 
Author Marçal Rusiñol; Farshad Nourbakhsh; Dimosthenis Karatzas; Ernest Valveny; Josep Llados
Title Perceptual Image Retrieval by Adding Color Information to the Shape Context Descriptor Type Conference Article
Year 2010 Publication 20th International Conference on Pattern Recognition Abbreviated Journal
Volume Issue Pages 1594–1597
Keywords
Abstract In this paper we present a method for the retrieval of images in terms of perceptual similarity. Local color information is added to the shape context descriptor in order to obtain an object description integrating both shape and color as visual cues. We use a color naming algorithm in order to represent the color information from a perceptual point of view. The proposed method has been tested in two different applications, an object retrieval scenario based on color sketch queries and a color trademark retrieval problem. Experimental results show that the addition of the color information significantly outperforms the sole use of the shape context descriptor.
Address Istanbul (Turkey)
Corporate Author Thesis
Publisher (up) 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 978-1-4244-7542-1 Medium
Area Expedition Conference ICPR
Notes DAG Approved no
Call Number DAG @ dag @ RNK2010 Serial 1435
Permanent link to this record
 

 
Author Farshad Nourbakhsh; Dimosthenis Karatzas; Ernest Valveny
Title A polar-based logo representation based on topological and colour features Type Conference Article
Year 2010 Publication 9th IAPR International Workshop on Document Analysis Systems Abbreviated Journal
Volume Issue Pages 341–348
Keywords
Abstract In this paper, we propose a novel rotation and scale invariant method for colour logo retrieval and classification, which involves performing a simple colour segmentation and subsequently describing each of the resultant colour components based on a set of topological and colour features. A polar representation is used to represent the logo and the subsequent logo matching is based on Cyclic Dynamic Time Warping (CDTW). We also show how combining information about the global distribution of the logo components and their local neighbourhood using the Delaunay triangulation allows to improve the results. All experiments are performed on a dataset of 2500 instances of 100 colour logo images in different rotations and scales.
Address Boston; USA;
Corporate Author Thesis
Publisher (up) Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 978-1-60558-773-8 Medium
Area Expedition Conference DAS
Notes DAG Approved no
Call Number DAG @ dag @ NKV2010 Serial 1436
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Author Sebastien Mace; Herve Locteau; Ernest Valveny; Salvatore Tabbone
Title A system to detect rooms in architectural floor plan images Type Conference Article
Year 2010 Publication 9th IAPR International Workshop on Document Analysis Systems Abbreviated Journal
Volume Issue Pages 167–174
Keywords
Abstract In this article, a system to detect rooms in architectural floor plan images is described. We first present a primitive extraction algorithm for line detection. It is based on an original coupling of classical Hough transform with image vectorization in order to perform robust and efficient line detection. We show how the lines that satisfy some graphical arrangements are combined into walls. We also present the way we detect some door hypothesis thanks to the extraction of arcs. Walls and door hypothesis are then used by our room segmentation strategy; it consists in recursively decomposing the image until getting nearly convex regions. The notion of convexity is difficult to quantify, and the selection of separation lines between regions can also be rough. We take advantage of knowledge associated to architectural floor plans in order to obtain mostly rectangular rooms. Qualitative and quantitative evaluations performed on a corpus of real documents show promising results.
Address Boston; USA
Corporate Author Thesis
Publisher (up) Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 978-1-60558-773-8 Medium
Area Expedition Conference DAS
Notes DAG Approved no
Call Number DAG @ dag @ MLV2010 Serial 1437
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Author Herve Locteau; Sebastien Mace; Ernest Valveny; Salvatore Tabbone
Title Extraction des pieces de un plan de habitation Type Conference Article
Year 2010 Publication Colloque Internacional Francophone de l´Ecrit et le Document Abbreviated Journal
Volume Issue Pages 1–12
Keywords
Abstract In this article, a method to extract the rooms of an architectural floor plan image is described. We first present a line detection algorithm to extract long lines in the image. Those lines are analyzed to identify the existing walls. From this point, room extraction can be seen as a classical segmentation task for which each region corresponds to a room. The chosen resolution strategy consists in recursively decomposing the image until getting nearly convex regions. The notion of convexity is difficult to quantify, and the selection of separation lines can also be rough. Thus, we take advantage of knowledge associated to architectural floor plans in order to obtain mainly rectangular rooms. Preliminary tests on a set of real documents show promising results.
Address Sousse, Tunisia
Corporate Author Thesis
Publisher (up) 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 DAG @ dag @ LMV2010 Serial 1440
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Author Joan Mas; Gemma Sanchez; Josep Llados
Title SSP: Sketching slide Presentations, a Syntactic Approach Type Conference Article
Year 2009 Publication 8th IAPR International Workshop on Graphics Recognition Abbreviated Journal
Volume Issue Pages
Keywords
Abstract The design of a slide presentation is a creative process. In this process first, humans visualize in their minds what they want to explain. Then, they have to be able to represent this knowledge in an understandable way. There exists a lot of commercial software that allows to create our own slide presentations but the creativity of the user is rather limited. In this article we present an application that allows the user to create and visualize a slide presentation from a sketch. A slide may be seen as a graphical document or a diagram where its elements are placed in a particular spatial arrangement. To describe and recognize slides a syntactic approach is proposed. This approach is based on an Adjacency Grammar and a parsing methodology to cope with this kind of grammars. The experimental evaluation shows the performance of our methodology from a qualitative and a quantitative point of view. Six different slides containing different number of symbols, from 4 to 7, have been given to the users and they have drawn them without restrictions in the order of the elements. The quantitative results give an idea on how suitable is our methodology to describe and recognize the different elements in a slide.
Address La Rochelle; France; July 2009
Corporate Author Thesis
Publisher (up) 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 @ MSL2009a Serial 1441
Permanent link to this record