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Author Sergio Escalera; Alicia Fornes; Oriol Pujol; Petia Radeva
Title Multi-class Binary Symbol Classification with Circular Blurred Shape Models Type Conference Article
Year 2009 Publication 15th International Conference on Image Analysis and Processing Abbreviated Journal
Volume 5716 Issue Pages 1005–1014
Keywords
Abstract Multi-class binary symbol classification requires the use of rich descriptors and robust classifiers. Shape representation is a difficult task because of several symbol distortions, such as occlusions, elastic deformations, gaps or noise. In this paper, we present the Circular Blurred Shape Model descriptor. This descriptor encodes the arrangement information of object parts in a correlogram structure. A prior blurring degree defines the level of distortion allowed to the symbol. Moreover, we learn the new feature space using a set of Adaboost classifiers, which are combined in the Error-Correcting Output Codes framework to deal with the multi-class categorization problem. The presented work has been validated over different multi-class data sets, and compared to the state-of-the-art descriptors, showing significant performance improvements.
Address Salerno, Italy
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title (down) LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-04145-7 Medium
Area Expedition Conference ICIAP
Notes MILAB;HuPBA;DAG Approved no
Call Number BCNPCL @ bcnpcl @ EFP2009c Serial 1186
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Author Maria Salamo; Sergio Escalera; Petia Radeva
Title Quality Enhancement based on Reinforcement Learning and Feature Weighting for a Critiquing-Based Recommender Type Conference Article
Year 2009 Publication 8th International Conference on Case-Based Reasoning Abbreviated Journal
Volume 5650 Issue Pages 298–312
Keywords
Abstract Personalizing the product recommendation task is a major focus of research in the area of conversational recommender systems. Conversational case-based recommender systems help users to navigate through product spaces, alternatively making product suggestions and eliciting users feedback. Critiquing is a common form of feedback and incremental critiquing-based recommender system has shown its efficiency to personalize products based primarily on a quality measure. This quality measure influences the recommendation process and it is obtained by the combination of compatibility and similarity scores. In this paper, we describe new compatibility strategies whose basis is on reinforcement learning and a new feature weighting technique which is based on the user’s history of critiques. Moreover, we show that our methodology can significantly improve recommendation efficiency in comparison with the state-of-the-art approaches.
Address Seattle, USA
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title (down) LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-02998-1 Medium
Area Expedition Conference ICCBR
Notes HuPBA; MILAB Approved no
Call Number BCNPCL @ bcnpcl @ SER2009 Serial 1187
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Author Mohammad Rouhani; Angel Sappa
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 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 (down) 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
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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 (down) 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 Marco Pedersoli; Jordi Gonzalez; Juan J. Villanueva
Title High-Speed Human Detection Using a Multiresolution Cascade of Histograms of Oriented Gradients Type Conference Article
Year 2009 Publication 4th Iberian Conference on Pattern Recognition and Image Analysis Abbreviated Journal
Volume 5524 Issue Pages
Keywords
Abstract This paper presents a new method for human detection based on a multiresolution cascade of Histograms of Oriented Gradients (HOG) that can highly reduce the computational cost of the detection search without affecting accuracy. The method consists of a cascade of sliding window detectors. Each detector is a Support Vector Machine (SVM) composed by features at different resolution, from coarse for the first level to fine for the last one.
Considering that the spatial stride of the sliding window search is affected by the HOG features size, unlike previous methods based on Adaboost cascades, we can adopt a spatial stride inversely proportional to the features resolution. This produces that the speed-up of the cascade is not only due to the low number of features that need to be computed in the first levels, but also to the lower number of detection windows that needs to be evaluated.
Experimental results shows that our method permits a detection rate comparable with the state of the art, but at the same time a gain in the speed of the detection search of 10-20 times depending on the cascade configuration.
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 (down) LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-02171-8 Medium
Area Expedition Conference IbPRIA
Notes ISE Approved no
Call Number ISE @ ise @ PGV2009 Serial 1214
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Author Bhaskar Chakraborty; Andrew Bagdanov; Jordi Gonzalez
Title Towards Real-Time Human Action Recognition Type Conference Article
Year 2009 Publication 4th Iberian Conference on Pattern Recognition and Image Analysis Abbreviated Journal
Volume 5524 Issue Pages
Keywords
Abstract This work presents a novel approach to human detection based action-recognition in real-time. To realize this goal our method first detects humans in different poses using a correlation-based approach. Recognition of actions is done afterward based on the change of the angular values subtended by various body parts. Real-time human detection and action recognition are very challenging, and most state-of-the-art approaches employ complex feature extraction and classification techniques, which ultimately becomes a handicap for real-time recognition. Our correlation-based method, on the other hand, is computationally efficient and uses very simple gradient-based features. For action recognition angular features of body parts are extracted using a skeleton technique. Results for action recognition are comparable with the present state-of-the-art.
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 (down) LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-02171-8 Medium
Area Expedition Conference IbPRIA
Notes ISE Approved no
Call Number DAG @ dag @ CBG2009 Serial 1215
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Author Murad Al Haj; Andrew Bagdanov; Jordi Gonzalez; Xavier Roca
Title Robust and Efficient Multipose Face Detection Using Skin Color Segmentation Type Conference Article
Year 2009 Publication 4th Iberian Conference on Pattern Recognition and Image Analysis Abbreviated Journal
Volume 5524 Issue Pages
Keywords
Abstract In this paper we describe an efficient technique for detecting faces in arbitrary images and video sequences. The approach is based on segmentation of images or video frames into skin-colored blobs using a pixel-based heuristic. Scale and translation invariant features are then computed from these segmented blobs which are used to perform statistical discrimination between face and non-face classes. We train and evaluate our method on a standard, publicly available database of face images and analyze its performance over a range of statistical pattern classifiers. The generalization of our approach is illustrated by testing on an independent sequence of frames containing many faces and non-faces. These experiments indicate that our proposed approach obtains false positive rates comparable to more complex, state-of-the-art techniques, and that it generalizes better to new data. Furthermore, the use of skin blobs and invariant features requires fewer training samples since significantly fewer non-face candidate regions must be considered when compared to AdaBoost-based approaches.
Address Springer Berlin Heidelberg
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title (down) LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-02171-8 Medium
Area Expedition Conference IbPRIA
Notes ISE Approved no
Call Number DAG @ dag @ ABG2009 Serial 1216
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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 (down) 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 Francesco Ciompi; Oriol Pujol; E Fernandez-Nofrerias; J. Mauri; Petia Radeva
Title ECOC Random Fields for Lumen Segmentation in Radial Artery IVUS Sequences Type Conference Article
Year 2009 Publication 12th International Conference on Medical Image and Computer Assisted Intervention Abbreviated Journal
Volume 5762 Issue II Pages
Keywords
Abstract The measure of lumen volume on radial arteries can be used to evaluate the vessel response to different vasodilators. In this paper, we present a framework for automatic lumen segmentation in longitudinal cut images of radial artery from Intravascular ultrasound sequences. The segmentation is tackled as a classification problem where the contextual information is exploited by means of Conditional Random Fields (CRFs). A multi-class classification framework is proposed, and inference is achieved by combining binary CRFs according to the Error-Correcting-Output-Code technique. The results are validated against manually segmented sequences. Finally, the method is compared with other state-of-the-art classifiers.
Address London, UK
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title (down) LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-04270-6 Medium
Area Expedition Conference MICCAI
Notes MILAB;HuPBA Approved no
Call Number BCNPCL @ bcnpcl @ CPF2009 Serial 1228
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Author David Aldavert; Ricardo Toledo; Arnau Ramisa; Ramon Lopez de Mantaras
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 Belgica
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title (down) 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
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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 (down) 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 Bogdan Raducanu; Fadi Dornaika
Title Natural Facial Expression Recognition Using Dynamic and Static Schemes Type Conference Article
Year 2009 Publication 5th International Symposium on Visual Computing Abbreviated Journal
Volume 5875 Issue Pages 730–739
Keywords
Abstract Affective computing is at the core of a new paradigm in HCI and AI represented by human-centered computing. Within this paradigm, it is expected that machines will be enabled with perceiving capabilities, making them aware about users’ affective state. The current paper addresses the problem of facial expression recognition from monocular videos sequences. We propose a dynamic facial expression recognition scheme, which is proven to be very efficient. Furthermore, it is conveniently compared with several static-based systems adopting different magnitude of facial expression. We provide evaluations of performance using Linear Discriminant Analysis (LDA), Non parametric Discriminant Analysis (NDA), and Support Vector Machines (SVM). We also provide performance evaluations using arbitrary test video sequences.
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 (down) LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-10330-8 Medium
Area Expedition Conference ISVC
Notes OR;MV Approved no
Call Number BCNPCL @ bcnpcl @ RaD2009 Serial 1257
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Author Santiago Segui; Laura Igual; Jordi Vitria
Title Weighted Bagging for Graph based One-Class Classifiers Type Conference Article
Year 2010 Publication 9th International Workshop on Multiple Classifier Systems Abbreviated Journal
Volume 5997 Issue Pages 1-10
Keywords
Abstract Most conventional learning algorithms require both positive and negative training data for achieving accurate classification results. However, the problem of learning classifiers from only positive data arises in many applications where negative data are too costly, difficult to obtain, or not available at all. Minimum Spanning Tree Class Descriptor (MSTCD) was presented as a method that achieves better accuracies than other one-class classifiers in high dimensional data. However, the presence of outliers in the target class severely harms the performance of this classifier. In this paper we propose two bagging strategies for MSTCD that reduce the influence of outliers in training data. We show the improved performance on both real and artificially contaminated data.
Address Cairo, Egypt
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title (down) LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-12126-5 Medium
Area Expedition Conference MCS
Notes MILAB;OR;MV Approved no
Call Number BCNPCL @ bcnpcl @ SIV2010 Serial 1284
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Author Susana Alvarez; Anna Salvatella; Maria Vanrell; Xavier Otazu
Title 3D Texton Spaces for color-texture retrieval Type Conference Article
Year 2010 Publication 7th International Conference on Image Analysis and Recognition Abbreviated Journal
Volume 6111 Issue Pages 354–363
Keywords
Abstract Color and texture are visual cues of different nature, their integration in an useful visual descriptor is not an easy problem. One way to combine both features is to compute spatial texture descriptors independently on each color channel. Another way is to do the integration at the descriptor level. In this case the problem of normalizing both cues arises. In this paper we solve the latest problem by fusing color and texture through distances in texton spaces. Textons are the attributes of image blobs and they are responsible for texture discrimination as defined in Julesz’s Texton theory. We describe them in two low-dimensional and uniform spaces, namely, shape and color. The dissimilarity between color texture images is computed by combining the distances in these two spaces. Following this approach, we propose our TCD descriptor which outperforms current state of art methods in the two different approaches mentioned above, early combination with LBP and late combination with MPEG-7. This is done on an image retrieval experiment over a highly diverse texture dataset from Corel.
Address
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor A.C. Campilho and M.S. Kamel
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title (down) LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-13771-6 Medium
Area Expedition Conference ICIAR
Notes CIC Approved no
Call Number CAT @ cat @ ASV2010a Serial 1325
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Author Naveen Onkarappa; Angel Sappa
Title On-Board Monocular Vision System Pose Estimation through a Dense Optical Flow Type Conference Article
Year 2010 Publication 7th International Conference on Image Analysis and Recognition Abbreviated Journal
Volume 6111 Issue Pages 230-239
Keywords
Abstract This paper presents a robust technique for estimating on-board monocular vision system pose. The proposed approach is based on a dense optical flow that is robust against shadows, reflections and illumination changes. A RANSAC based scheme is used to cope with the outliers in the optical flow. The proposed technique is intended to be used in driver assistance systems for applications such as obstacle or pedestrian detection. Experimental results on different scenarios, both from synthetic and real sequences, shows usefulness of the proposed approach.
Address Povoa 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 (down) LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-13771-6 Medium
Area Expedition Conference ICIAR
Notes ADAS Approved no
Call Number ADAS @ adas @ OnS2010 Serial 1342
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