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| Author | Andreas Møgelmose; Chris Bahnsen; Thomas B. Moeslund; Albert Clapes; Sergio Escalera | ||||
| Title | Tri-modal Person Re-identification with RGB, Depth and Thermal Features | Type | Conference Article | ||
| Year | 2013 | Publication | 9th IEEE Workshop on Perception beyond the visible Spectrum, Computer Vision and Pattern Recognition | Abbreviated Journal  |
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| Volume | Issue | Pages | 301-307 | ||
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| Abstract | Person re-identification is about recognizing people who have passed by a sensor earlier. Previous work is mainly based on RGB data, but in this work we for the first time present a system where we combine RGB, depth, and thermal data for re-identification purposes. First, from each of the three modalities, we obtain some particular features: from RGB data, we model color information from different regions of the body, from depth data, we compute different soft body biometrics, and from thermal data, we extract local structural information. Then, the three information types are combined in a joined classifier. The tri-modal system is evaluated on a new RGB-D-T dataset, showing successful results in re-identification scenarios. | ||||
| Address | Portland; oregon; June 2013 | ||||
| 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 | 978-0-7695-4990-3 | Medium | ||
| Area | Expedition | Conference | CVPRW | ||
| Notes | HUPBA;MILAB | Approved | no | ||
| Call Number | Admin @ si @ MBM2013 | Serial | 2253 | ||
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| Author | Daniel Sanchez; J.C.Ortega; Miguel Angel Bautista | ||||
| Title | Human Body Segmentation with Multi-limb Error-Correcting Output Codes Detection and Graph Cuts Optimization | Type | Conference Article | ||
| Year | 2013 | Publication | 6th Iberian Conference on Pattern Recognition and Image Analysis | Abbreviated Journal |
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| Volume | 7887 | Issue | Pages | 50-58 | |
| Keywords | Human Body Segmentation; Error-Correcting Output Codes; Cascade of Classifiers; Graph Cuts | ||||
| Abstract | Human body segmentation is a hard task because of the high variability in appearance produced by changes in the point of view, lighting conditions, and number of articulations of the human body. In this paper, we propose a two-stage approach for the segmentation of the human body. In a first step, a set of human limbs are described, normalized to be rotation invariant, and trained using cascade of classifiers to be split in a tree structure way. Once the tree structure is trained, it is included in a ternary Error-Correcting Output Codes (ECOC) framework. This first classification step is applied in a windowing way on a new test image, defining a body-like probability map, which is used as an initialization of a GMM color modelling and binary Graph Cuts optimization procedure. The proposed methodology is tested in a novel limb-labelled data set. Results show performance improvements of the novel approach in comparison to classical cascade of classifiers and human detector-based Graph Cuts segmentation approaches. | ||||
| Address | Madeira; Portugal; June 2013 | ||||
| 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 | 978-3-642-38627-5 | Medium | |
| Area | Expedition | Conference | IbPRIA | ||
| Notes | HUPBA | Approved | no | ||
| Call Number | SOB2013 | Serial | 2250 | ||
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| Author | Mohammad Ali Bagheri; Qigang Gao; Sergio Escalera | ||||
| Title | Logo recognition Based on the Dempster-Shafer Fusion of Multiple Classifiers | Type | Conference Article | ||
| Year | 2013 | Publication | 26th Canadian Conference on Artificial Intelligence | Abbreviated Journal |
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| Volume | 7884 | Issue | Pages | 1-12 | |
| Keywords | Logo recognition; ensemble classification; Dempster-Shafer fusion; Zernike moments; generic Fourier descriptor; shape signature | ||||
| Abstract | Best paper award
The performance of different feature extraction and shape description methods in trademark image recognition systems have been studied by several researchers. However, the potential improvement in classification through feature fusion by ensemble-based methods has remained unattended. In this work, we evaluate the performance of an ensemble of three classifiers, each trained on different feature sets. Three promising shape description techniques, including Zernike moments, generic Fourier descriptors, and shape signature are used to extract informative features from logo images, and each set of features is fed into an individual classifier. In order to reduce recognition error, a powerful combination strategy based on the Dempster-Shafer theory is utilized to fuse the three classifiers trained on different sources of information. This combination strategy can effectively make use of diversity of base learners generated with different set of features. The recognition results of the individual classifiers are compared with those obtained from fusing the classifiers’ output, showing significant performance improvements of the proposed methodology. |
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| Address | Canada; May 2013 | ||||
| Corporate Author | Thesis | ||||
| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0302-9743 | ISBN | 978-3-642-38456-1 | Medium | |
| Area | Expedition | Conference | AI | ||
| Notes | HuPBA;MILAB | Approved | no | ||
| Call Number | Admin @ si @ BGE2013b | Serial | 2249 | ||
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| Author | Naveen Onkarappa; Angel Sappa | ||||
| Title | Laplacian Derivative based Regularization for Optical Flow Estimation in Driving Scenario | Type | Conference Article | ||
| Year | 2013 | Publication | 15th International Conference on Computer Analysis of Images and Patterns | Abbreviated Journal |
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| Volume | 8048 | Issue | Pages | 483-490 | |
| Keywords | Optical flow; regularization; Driver Assistance Systems; Performance Evaluation | ||||
| Abstract | Existing state of the art optical flow approaches, which are evaluated on standard datasets such as Middlebury, not necessarily have a similar performance when evaluated on driving scenarios. This drop on performance is due to several challenges arising on real scenarios during driving. Towards this direction, in this paper, we propose a modification to the regularization term in a variational optical flow formulation, that notably improves the results, specially in driving scenarios. The proposed modification consists on using the Laplacian derivatives of flow components in the regularization term instead of gradients of flow components. We show the improvements in results on a standard real image sequences dataset (KITTI). | ||||
| Address | York; UK; August 2013 | ||||
| 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 | 978-3-642-40245-6 | Medium | |
| Area | Expedition | Conference | CAIP | ||
| Notes | ADAS; 600.055; 601.215 | Approved | no | ||
| Call Number | Admin @ si @ OnS2013b | Serial | 2244 | ||
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| Author | Alicia Fornes; Xavier Otazu; Josep Llados | ||||
| Title | Show through cancellation and image enhancement by multiresolution contrast processing | Type | Conference Article | ||
| Year | 2013 | Publication | 12th International Conference on Document Analysis and Recognition | Abbreviated Journal |
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| Volume | Issue | Pages | 200-204 | ||
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| Abstract | Historical documents suffer from different types of degradation and noise such as background variation, uneven illumination or dark spots. In case of double-sided documents, another common problem is that the back side of the document usually interferes with the front side because of the transparency of the document or ink bleeding. This effect is called the show through phenomenon. Many methods are developed to solve these problems, and in the case of show-through, by scanning and matching both the front and back sides of the document. In contrast, our approach is designed to use only one side of the scanned document. We hypothesize that show-trough are low contrast components, while foreground components are high contrast ones. A Multiresolution Contrast (MC) decomposition is presented in order to estimate the contrast of features at different spatial scales. We cancel the show-through phenomenon by thresholding these low contrast components. This decomposition is also able to enhance the image removing shadowed areas by weighting spatial scales. Results show that the enhanced images improve the readability of the documents, allowing scholars both to recover unreadable words and to solve ambiguities. | ||||
| Address | Washington; USA; August 2013 | ||||
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| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1520-5363 | ISBN | Medium | ||
| Area | Expedition | Conference | ICDAR | ||
| Notes | DAG; 602.006; 600.045; 600.061; 600.052;CIC | Approved | no | ||
| Call Number | Admin @ si @ FOL2013 | Serial | 2241 | ||
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| Author | Sandra Jimenez; Xavier Otazu; Valero Laparra; Jesus Malo | ||||
| Title | Chromatic induction and contrast masking: similar models, different goals? | Type | Conference Article | ||
| Year | 2013 | Publication | Human Vision and Electronic Imaging XVIII | Abbreviated Journal |
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| Volume | 8651 | Issue | Pages | ||
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| Abstract | Normalization of signals coming from linear sensors is an ubiquitous mechanism of neural adaptation.1 Local interaction between sensors tuned to a particular feature at certain spatial position and neighbor sensors explains a wide range of psychophysical facts including (1) masking of spatial patterns, (2) non-linearities of motion sensors, (3) adaptation of color perception, (4) brightness and chromatic induction, and (5) image quality assessment. Although the above models have formal and qualitative similarities, it does not necessarily mean that the mechanisms involved are pursuing the same statistical goal. For instance, in the case of chromatic mechanisms (disregarding spatial information), different parameters in the normalization give rise to optimal discrimination or adaptation, and different non-linearities may give rise to error minimization or component independence. In the case of spatial sensors (disregarding color information), a number of studies have pointed out the benefits of masking in statistical independence terms. However, such statistical analysis has not been performed for spatio-chromatic induction models where chromatic perception depends on spatial configuration. In this work we investigate whether successful spatio-chromatic induction models,6 increase component independence similarly as previously reported for masking models. Mutual information analysis suggests that seeking an efficient chromatic representation may explain the prevalence of induction effects in spatially simple images. © (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only. | ||||
| Address | San Francisco CA; USA; February 2013 | ||||
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| ISSN | ISBN | Medium | |||
| Area | Expedition | Conference | HVEI | ||
| Notes | CIC | Approved | no | ||
| Call Number | Admin @ si @ JOL2013 | Serial | 2240 | ||
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| Author | Santiago Segui; Michal Drozdzal; Ekaterina Zaytseva; Carolina Malagelada; Fernando Azpiroz; Petia Radeva; Jordi Vitria | ||||
| Title | A new image centrality descriptor for wrinkle frame detection in WCE videos | Type | Conference Article | ||
| Year | 2013 | Publication | 13th IAPR Conference on Machine Vision Applications | Abbreviated Journal |
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| Abstract | Small bowel motility dysfunctions are a widespread functional disorder characterized by abdominal pain and altered bowel habits in the absence of specific and unique organic pathology. Current methods of diagnosis are complex and can only be conducted at some highly specialized referral centers. Wireless Video Capsule Endoscopy (WCE) could be an interesting diagnostic alternative that presents excellent clinical advantages, since it is non-invasive and can be conducted by non specialists. The purpose of this work is to present a new method for the detection of wrinkle frames in WCE, a critical characteristic to detect one of the main motility events: contractions. The method goes beyond the use of one of the classical image feature, the Histogram | ||||
| Address | Kyoto; Japan; May 2013 | ||||
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| Area | Expedition | Conference | MVA | ||
| Notes | OR; MILAB; 600.046;MV | Approved | no | ||
| Call Number | Admin @ si @ SDZ2013 | Serial | 2239 | ||
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| Author | Xavier Baro; David Masip; Elena Planas; Julia Minguillon | ||||
| Title | PeLP: Plataforma para el Aprendizaje de Lenguajes de Programación | Type | Miscellaneous | ||
| Year | 2013 | Publication | XV Jornadas de Enseñanza Universitaria de la Informatica | Abbreviated Journal |
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| Area | Expedition | Conference | JENUI | ||
| Notes | OR;HuPBA;MV | Approved | no | ||
| Call Number | Admin @ si @ BMP2013 | Serial | 2237 | ||
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| Author | Victor Borjas; Jordi Vitria; Petia Radeva | ||||
| Title | Gradient Histogram Background Modeling for People Detection in Stationary Camera Environments | Type | Conference Article | ||
| Year | 2013 | Publication | 13th IAPR Conference on Machine Vision Applications | Abbreviated Journal |
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| Abstract | Best Poster AwardOne of the big challenges of today person detectors is the decreasing of the false positive rate. In this paper, we propose a novel framework to customize person detectors in static camera scenarios in order to reduce this rate. This scheme includes background modeling for subtraction based on gradient histograms and Mean-Shift clustering. Our experiments show that the detection improved compared to using only the output from the pedestrian detector reducing 87% of the false positives and therefore the overall precision of the detection
was increased signi cantly. |
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| Address | Kyoto; Japan; May 2013 | ||||
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| Publisher | Place of Publication | Editor | |||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
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| ISSN | ISBN | Medium | |||
| Area | Expedition | Conference | MVA | ||
| Notes | OR; MILAB;MV | Approved | no | ||
| Call Number | BVR2013 | Serial | 2238 | ||
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| Author | Fadi Dornaika; Bogdan Raducanu | ||||
| Title | Out-of-Sample Embedding for Manifold Learning Applied to Face Recognition | Type | Conference Article | ||
| Year | 2013 | Publication | IEEE International Workshop on Analysis and Modeling of Faces and Gestures | Abbreviated Journal |
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| Volume | Issue | Pages | 862-868 | ||
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| Abstract | Manifold learning techniques are affected by two critical aspects: (i) the design of the adjacency graphs, and (ii) the embedding of new test data---the out-of-sample problem. For the first aspect, the proposed schemes were heuristically driven. For the second aspect, the difficulty resides in finding an accurate mapping that transfers unseen data samples into an existing manifold. Past works addressing these two aspects were heavily parametric in the sense that the optimal performance is only reached for a suitable parameter choice that should be known in advance. In this paper, we demonstrate that sparse coding theory not only serves for automatic graph reconstruction as shown in recent works, but also represents an accurate alternative for out-of-sample embedding. Considering for a case study the Laplacian Eigenmaps, we applied our method to the face recognition problem. To evaluate the effectiveness of the proposed out-of-sample embedding, experiments are conducted using the k-nearest neighbor (KNN) and Kernel Support Vector Machines (KSVM) classifiers on four public face databases. The experimental results show that the proposed model is able to achieve high categorization effectiveness as well as high consistency with non-linear embeddings/manifolds obtained in batch modes. | ||||
| Address | Portland; USA; June 2013 | ||||
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| Area | Expedition | Conference | CVPRW | ||
| Notes | OR; 600.046;MV | Approved | no | ||
| Call Number | Admin @ si @ DoR2013 | Serial | 2236 | ||
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| Author | Michal Drozdzal; Santiago Segui; Petia Radeva; Carolina Malagelada; Fernando Azpiroz; Jordi Vitria | ||||
| Title | An Application for Efficient Error-Free Labeling of Medical Images | Type | Book Chapter | ||
| Year | 2013 | Publication | Multimodal Interaction in Image and Video Applications | Abbreviated Journal |
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| Volume | 48 | Issue | Pages | 1-16 | |
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| Abstract | In this chapter we describe an application for efficient error-free labeling of medical images. In this scenario, the compilation of a complete training set for building a realistic model of a given class of samples is not an easy task, making the process tedious and time consuming. For this reason, there is a need for interactive labeling applications that minimize the effort of the user while providing error-free labeling. We propose a new algorithm that is based on data similarity in feature space. This method actively explores data in order to find the best label-aligned clustering and exploits it to reduce the labeler effort, that is measured by the number of “clicks. Moreover, error-free labeling is guaranteed by the fact that all data and their labels proposals are visually revised by en expert. | ||||
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| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1868-4394 | ISBN | 978-3-642-35931-6 | Medium | |
| Area | Expedition | Conference | |||
| Notes | MILAB; OR;MV | Approved | no | ||
| Call Number | Admin @ si @ DSR2013 | Serial | 2235 | ||
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| Author | German Ros; J. Guerrero; Angel Sappa; Antonio Lopez | ||||
| Title | VSLAM pose initialization via Lie groups and Lie algebras optimization | Type | Conference Article | ||
| Year | 2013 | Publication | Proceedings of IEEE International Conference on Robotics and Automation | Abbreviated Journal |
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| Volume | Issue | Pages | 5740 - 5747 | ||
| Keywords | SLAM | ||||
| Abstract | We present a novel technique for estimating initial 3D poses in the context of localization and Visual SLAM problems. The presented approach can deal with noise, outliers and a large amount of input data and still performs in real time in a standard CPU. Our method produces solutions with an accuracy comparable to those produced by RANSAC but can be much faster when the percentage of outliers is high or for large amounts of input data. On the current work we propose to formulate the pose estimation as an optimization problem on Lie groups, considering their manifold structure as well as their associated Lie algebras. This allows us to perform a fast and simple optimization at the same time that conserve all the constraints imposed by the Lie group SE(3). Additionally, we present several key design concepts related with the cost function and its Jacobian; aspects that are critical for the good performance of the algorithm. | ||||
| Address | Karlsruhe; Germany; May 2013 | ||||
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| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1050-4729 | ISBN | 978-1-4673-5641-1 | Medium | |
| Area | Expedition | Conference | ICRA | ||
| Notes | ADAS; 600.054; 600.055; 600.057 | Approved | no | ||
| Call Number | Admin @ si @ RGS2013a; ADAS @ adas @ | Serial | 2225 | ||
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| Author | David Aldavert; Marçal Rusiñol; Ricardo Toledo; Josep Llados | ||||
| Title | Integrating Visual and Textual Cues for Query-by-String Word Spotting | Type | Conference Article | ||
| Year | 2013 | Publication | 12th International Conference on Document Analysis and Recognition | Abbreviated Journal |
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| Volume | Issue | Pages | 511 - 515 | ||
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| Abstract | In this paper, we present a word spotting framework that follows the query-by-string paradigm where word images are represented both by textual and visual representations. The textual representation is formulated in terms of character $n$-grams while the visual one is based on the bag-of-visual-words scheme. These two representations are merged together and projected to a sub-vector space. This transform allows to, given a textual query, retrieve word instances that were only represented by the visual modality. Moreover, this statistical representation can be used together with state-of-the-art indexation structures in order to deal with large-scale scenarios. The proposed method is evaluated using a collection of historical documents outperforming state-of-the-art performances. | ||||
| Address | Washington; USA; August 2013 | ||||
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| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1520-5363 | ISBN | Medium | ||
| Area | Expedition | Conference | ICDAR | ||
| Notes | DAG; ADAS; 600.045; 600.055; 600.061 | Approved | no | ||
| Call Number | Admin @ si @ ART2013 | Serial | 2224 | ||
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| Author | Ariel Amato; Ivan Huerta; Mikhail Mozerov; Xavier Roca; Jordi Gonzalez | ||||
| Title | Moving Cast Shadows Detection Methods for Video Surveillance Applications | Type | Book Chapter | ||
| Year | 2014 | Publication | Augmented Vision and Reality | Abbreviated Journal |
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| Volume | 6 | Issue | Pages | 23-47 | |
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| Abstract | Moving cast shadows are a major concern in today’s performance from broad range of many vision-based surveillance applications because they highly difficult the object classification task. Several shadow detection methods have been reported in the literature during the last years. They are mainly divided into two domains. One usually works with static images, whereas the second one uses image sequences, namely video content. In spite of the fact that both cases can be analogously analyzed, there is a difference in the application field. The first case, shadow detection methods can be exploited in order to obtain additional geometric and semantic cues about shape and position of its casting object (‘shape from shadows’) as well as the localization of the light source. While in the second one, the main purpose is usually change detection, scene matching or surveillance (usually in a background subtraction context). Shadows can in fact modify in a negative way the shape and color of the target object and therefore affect the performance of scene analysis and interpretation in many applications. This chapter wills mainly reviews shadow detection methods as well as their taxonomies related with the second case, thus aiming at those shadows which are associated with moving objects (moving shadows). | ||||
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| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 2190-5916 | ISBN | 978-3-642-37840-9 | Medium | |
| Area | Expedition | Conference | |||
| Notes | ISE; 605.203; 600.049; 302.018; 302.012; 600.078 | Approved | no | ||
| Call Number | Admin @ si @ AHM2014 | Serial | 2223 | ||
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| Author | Marc Castello; Jordi Gonzalez; Ariel Amato; Pau Baiget; Carles Fernandez; Josep M. Gonfaus; Ramon Mollineda; Marco Pedersoli; Nicolas Perez de la Blanca; Xavier Roca | ||||
| Title | Exploiting Multimodal Interaction Techniques for Video-Surveillance | Type | Book Chapter | ||
| Year | 2013 | Publication | Multimodal Interaction in Image and Video Applications Intelligent Systems Reference Library | Abbreviated Journal |
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| Volume | 48 | Issue | 8 | Pages | 135-151 |
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| Abstract | In this paper we present an example of a video surveillance application that exploits Multimodal Interactive (MI) technologies. The main objective of the so-called VID-Hum prototype was to develop a cognitive artificial system for both the detection and description of a particular set of human behaviours arising from real-world events. The main procedure of the prototype described in this chapter entails: (i) adaptation, since the system adapts itself to the most common behaviours (qualitative data) inferred from tracking (quantitative data) thus being able to recognize abnormal behaviors; (ii) feedback, since an advanced interface based on Natural Language understanding allows end-users the communicationwith the prototype by means of conceptual sentences; and (iii) multimodality, since a virtual avatar has been designed to describe what is happening in the scene, based on those textual interpretations generated by the prototype. Thus, the MI methodology has provided an adequate framework for all these cooperating processes. | ||||
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| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1868-4394 | ISBN | 978-3-642-35931-6 | Medium | |
| Area | Expedition | Conference | |||
| Notes | ISE; 605.203; 600.049 | Approved | no | ||
| Call Number | CGA2013 | Serial | 2222 | ||
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