| Records |
| Author |
Veronica Romero; Alicia Fornes; Nicolas Serrano; Joan Andreu Sanchez; A.H. Toselli; Volkmar Frinken; E. Vidal; Josep Llados |
| Title |
The ESPOSALLES database: An ancient marriage license corpus for off-line handwriting recognition |
Type |
Journal Article |
| Year |
2013 |
Publication |
Pattern Recognition |
Abbreviated Journal |
PR |
Volume  |
46 |
Issue |
6 |
Pages |
1658-1669 |
| Keywords |
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| Abstract |
Historical records of daily activities provide intriguing insights into the life of our ancestors, useful for demography studies and genealogical research. Automatic processing of historical documents, however, has mostly been focused on single works of literature and less on social records, which tend to have a distinct layout, structure, and vocabulary. Such information is usually collected by expert demographers that devote a lot of time to manually transcribe them. This paper presents a new database, compiled from a marriage license books collection, to support research in automatic handwriting recognition for historical documents containing social records. Marriage license books are documents that were used for centuries by ecclesiastical institutions to register marriage licenses. Books from this collection are handwritten and span nearly half a millennium until the beginning of the 20th century. In addition, a study is presented about the capability of state-of-the-art handwritten text recognition systems, when applied to the presented database. Baseline results are reported for reference in future studies. |
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Elsevier Science Inc. New York, NY, USA |
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0031-3203 |
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Expedition |
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Conference |
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| Notes |
DAG; 600.045; 602.006; 605.203 |
Approved |
no |
| Call Number |
Admin @ si @ RFS2013 |
Serial |
2298 |
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| Author |
Mohammad Ali Bagheri; Qigang Gao; Sergio Escalera |
| Title |
A Genetic-based Subspace Analysis Method for Improving Error-Correcting Output Coding |
Type |
Journal Article |
| Year |
2013 |
Publication |
Pattern Recognition |
Abbreviated Journal |
PR |
| Volume |
46 |
Issue |
10 |
Pages |
2830-2839 |
| Keywords |
Error Correcting Output Codes; Evolutionary computation; Multiclass classification; Feature subspace; Ensemble classification |
| Abstract |
Two key factors affecting the performance of Error Correcting Output Codes (ECOC) in multiclass classification problems are the independence of binary classifiers and the problem-dependent coding design. In this paper, we propose an evolutionary algorithm-based approach to the design of an application-dependent codematrix in the ECOC framework. The central idea of this work is to design a three-dimensional codematrix, where the third dimension is the feature space of the problem domain. In order to do that, we consider the feature space in the design process of the codematrix with the aim of improving the independence and accuracy of binary classifiers. The proposed method takes advantage of some basic concepts of ensemble classification, such as diversity of classifiers, and also benefits from the evolutionary approach for optimizing the three-dimensional codematrix, taking into account the problem domain. We provide a set of experimental results using a set of benchmark datasets from the UCI Machine Learning Repository, as well as two real multiclass Computer Vision problems. Both sets of experiments are conducted using two different base learners: Neural Networks and Decision Trees. The results show that the proposed method increases the classification accuracy in comparison with the state-of-the-art ECOC coding techniques. |
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Elsevier |
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Edition |
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0031-3203 |
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Conference |
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| Notes |
HuPBA;MILAB |
Approved |
no |
| Call Number |
Admin @ si @ BGE2013a |
Serial |
2247 |
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| Author |
Muhammad Muzzamil Luqman; Jean-Yves Ramel; Josep Llados; Thierry Brouard |
| Title |
Fuzzy Multilevel Graph Embedding |
Type |
Journal Article |
| Year |
2013 |
Publication |
Pattern Recognition |
Abbreviated Journal |
PR |
| Volume |
46 |
Issue |
2 |
Pages |
551-565 |
| Keywords |
Pattern recognition; Graphics recognition; Graph clustering; Graph classification; Explicit graph embedding; Fuzzy logic |
| Abstract |
Structural pattern recognition approaches offer the most expressive, convenient, powerful but computational expensive representations of underlying relational information. To benefit from mature, less expensive and efficient state-of-the-art machine learning models of statistical pattern recognition they must be mapped to a low-dimensional vector space. Our method of explicit graph embedding bridges the gap between structural and statistical pattern recognition. We extract the topological, structural and attribute information from a graph and encode numeric details by fuzzy histograms and symbolic details by crisp histograms. The histograms are concatenated to achieve a simple and straightforward embedding of graph into a low-dimensional numeric feature vector. Experimentation on standard public graph datasets shows that our method outperforms the state-of-the-art methods of graph embedding for richly attributed graphs. |
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Elsevier |
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0031-3203 |
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Conference |
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| Notes |
DAG; 600.042; 600.045; 605.203 |
Approved |
no |
| Call Number |
Admin @ si @ LRL2013a |
Serial |
2270 |
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| Author |
Anjan Dutta; Josep Llados; Umapada Pal |
| Title |
A symbol spotting approach in graphical documents by hashing serialized graphs |
Type |
Journal Article |
| Year |
2013 |
Publication |
Pattern Recognition |
Abbreviated Journal |
PR |
| Volume |
46 |
Issue |
3 |
Pages |
752-768 |
| Keywords |
Symbol spotting; Graphics recognition; Graph matching; Graph serialization; Graph factorization; Graph paths; Hashing |
| Abstract |
In this paper we propose a symbol spotting technique in graphical documents. Graphs are used to represent the documents and a (sub)graph matching technique is used to detect the symbols in them. We propose a graph serialization to reduce the usual computational complexity of graph matching. Serialization of graphs is performed by computing acyclic graph paths between each pair of connected nodes. Graph paths are one-dimensional structures of graphs which are less expensive in terms of computation. At the same time they enable robust localization even in the presence of noise and distortion. Indexing in large graph databases involves a computational burden as well. We propose a graph factorization approach to tackle this problem. Factorization is intended to create a unified indexed structure over the database of graphical documents. Once graph paths are extracted, the entire database of graphical documents is indexed in hash tables by locality sensitive hashing (LSH) of shape descriptors of the paths. The hashing data structure aims to execute an approximate k-NN search in a sub-linear time. We have performed detailed experiments with various datasets of line drawings and compared our method with the state-of-the-art works. The results demonstrate the effectiveness and efficiency of our technique. |
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Elsevier |
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Edition |
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0031-3203 |
ISBN |
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Expedition |
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Conference |
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| Notes |
DAG; 600.042; 600.045; 605.203; 601.152 |
Approved |
no |
| Call Number |
Admin @ si @ DLP2012 |
Serial |
2127 |
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| Author |
Zeynep Yucel; Albert Ali Salah; Çetin Meriçli; Tekin Meriçli; Roberto Valenti; Theo Gevers |
| Title |
Joint Attention by Gaze Interpolation and Saliency |
Type |
Journal |
| Year |
2013 |
Publication |
IEEE Transactions on cybernetics |
Abbreviated Journal |
T-CIBER |
| Volume |
43 |
Issue |
3 |
Pages |
829-842 |
| Keywords |
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| Abstract |
Joint attention, which is the ability of coordination of a common point of reference with the communicating party, emerges as a key factor in various interaction scenarios. This paper presents an image-based method for establishing joint attention between an experimenter and a robot. The precise analysis of the experimenter's eye region requires stability and high-resolution image acquisition, which is not always available. We investigate regression-based interpolation of the gaze direction from the head pose of the experimenter, which is easier to track. Gaussian process regression and neural networks are contrasted to interpolate the gaze direction. Then, we combine gaze interpolation with image-based saliency to improve the target point estimates and test three different saliency schemes. We demonstrate the proposed method on a human-robot interaction scenario. Cross-subject evaluations, as well as experiments under adverse conditions (such as dimmed or artificial illumination or motion blur), show that our method generalizes well and achieves rapid gaze estimation for establishing joint attention. |
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Edition |
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| ISSN |
2168-2267 |
ISBN |
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Medium |
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Conference |
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| Notes |
ALTRES;ISE |
Approved |
no |
| Call Number |
Admin @ si @ YSM2013 |
Serial |
2363 |
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| Author |
J.S. Cope; P.Remagnino; S.Mannan; Katerine Diaz; Francesc J. Ferri; P.Wilkin |
| Title |
Reverse Engineering Expert Visual Observations: From Fixations To The Learning Of Spatial Filters With A Neural-Gas Algorithm |
Type |
Journal Article |
| Year |
2013 |
Publication |
Expert Systems with Applications |
Abbreviated Journal |
EXWA |
| Volume |
40 |
Issue |
17 |
Pages |
6707-6712 |
| Keywords |
Neural gas; Expert vision; Eye-tracking; Fixations |
| Abstract |
Human beings can become experts in performing specific vision tasks, for example, doctors analysing medical images, or botanists studying leaves. With sufficient knowledge and experience, people can become very efficient at such tasks. When attempting to perform these tasks with a machine vision system, it would be highly beneficial to be able to replicate the process which the expert undergoes. Advances in eye-tracking technology can provide data to allow us to discover the manner in which an expert studies an image. This paper presents a first step towards utilizing these data for computer vision purposes. A growing-neural-gas algorithm is used to learn a set of Gabor filters which give high responses to image regions which a human expert fixated on. These filters can then be used to identify regions in other images which are likely to be useful for a given vision task. The algorithm is evaluated by learning filters for locating specific areas of plant leaves. |
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Edition |
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| ISSN |
0957-4174 |
ISBN |
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Medium |
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| Notes |
ADAS |
Approved |
no |
| Call Number |
Admin @ si @ CRM2013 |
Serial |
2438 |
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| Author |
Marina Alberti; Simone Balocco; Xavier Carrillo; J. Mauri; Petia Radeva |
| Title |
Automatic non-rigid temporal alignment of IVUS sequences: method and quantitative validation |
Type |
Journal Article |
| Year |
2013 |
Publication |
Ultrasound in Medicine and Biology |
Abbreviated Journal |
UMB |
| Volume |
39 |
Issue |
9 |
Pages |
1698-712 |
| Keywords |
Intravascular ultrasound; Dynamic time warping; Non-rigid alignment; Sequence matching; Partial overlapping strategy |
| Abstract |
Clinical studies on atherosclerosis regression/progression performed by intravascular ultrasound analysis would benefit from accurate alignment of sequences of the same patient before and after clinical interventions and at follow-up. In this article, a methodology for automatic alignment of intravascular ultrasound sequences based on the dynamic time warping technique is proposed. The non-rigid alignment is adapted to the specific task by applying it to multidimensional signals describing the morphologic content of the vessel. Moreover, dynamic time warping is embedded into a framework comprising a strategy to address partial overlapping between acquisitions and a term that regularizes non-physiologic temporal compression/expansion of the sequences. Extensive validation is performed on both synthetic and in vivo data. The proposed method reaches alignment errors of approximately 0.43 mm for pairs of sequences acquired during the same intervention phase and 0.77 mm for pairs of sequences acquired at successive intervention stages. |
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| Notes |
MILAB |
Approved |
no |
| Call Number |
Admin @ si @ ABC2013 |
Serial |
2313 |
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| Author |
Kaida Xiao; Chenyang Fu; D.Mylonas; Dimosthenis Karatzas; S. Wuerger |
| Title |
Unique Hue Data for Colour Appearance Models. Part ii: Chromatic Adaptation Transform |
Type |
Journal Article |
| Year |
2013 |
Publication |
Color Research & Application |
Abbreviated Journal |
CRA |
| Volume |
38 |
Issue |
1 |
Pages |
22-29 |
| Keywords |
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| Abstract |
Unique hue settings of 185 observers under three room-lighting conditions were used to evaluate the accuracy of full and mixed chromatic adaptation transform models of CIECAM02 in terms of unique hue reproduction. Perceptual hue shifts in CIECAM02 were evaluated for both models with no clear difference using the current Commission Internationale de l'Éclairage (CIE) recommendation for mixed chromatic adaptation ratio. Using our large dataset of unique hue data as a benchmark, an optimised parameter is proposed for chromatic adaptation under mixed illumination conditions that produces more accurate results in unique hue reproduction. © 2011 Wiley Periodicals, Inc. Col Res Appl, 2013 |
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DAG |
Approved |
no |
| Call Number |
Admin @ si @ XFM2013 |
Serial |
1822 |
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| Author |
Laura Igual; Agata Lapedriza; Ricard Borras |
| Title |
Robust Gait-Based Gender Classification using Depth Cameras |
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Journal Article |
| Year |
2013 |
Publication |
EURASIP Journal on Advances in Signal Processing |
Abbreviated Journal |
EURASIPJ |
| Volume |
37 |
Issue |
1 |
Pages |
72-80 |
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| Abstract |
This article presents a new approach for gait-based gender recognition using depth cameras, that can run in real time. The main contribution of this study is a new fast feature extraction strategy that uses the 3D point cloud obtained from the frames in a gait cycle. For each frame, these points are aligned according to their centroid and grouped. After that, they are projected into their PCA plane, obtaining a representation of the cycle particularly robust against view changes. Then, final discriminative features are computed by first making a histogram of the projected points and then using linear discriminant analysis. To test the method we have used the DGait database, which is currently the only publicly available database for gait analysis that includes depth information. We have performed experiments on manually labeled cycles and over whole video sequences, and the results show that our method improves the accuracy significantly, compared with state-of-the-art systems which do not use depth information. Furthermore, our approach is insensitive to illumination changes, given that it discards the RGB information. That makes the method especially suitable for real applications, as illustrated in the last part of the experiments section. |
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| Notes |
MILAB; OR;MV |
Approved |
no |
| Call Number |
Admin @ si @ ILB2013 |
Serial |
2144 |
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| Author |
Michal Drozdzal; Santiago Segui; Carolina Malagelada; Fernando Azpiroz; Petia Radeva |
| Title |
Adaptable image cuts for motility inspection using WCE |
Type |
Journal Article |
| Year |
2013 |
Publication |
Computerized Medical Imaging and Graphics |
Abbreviated Journal |
CMIG |
| Volume |
37 |
Issue |
1 |
Pages |
72-80 |
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| Abstract |
The Wireless Capsule Endoscopy (WCE) technology allows the visualization of the whole small intestine tract. Since the capsule is freely moving, mainly by the means of peristalsis, the data acquired during the study gives a lot of information about the intestinal motility. However, due to: (1) huge amount of frames, (2) complex intestinal scene appearance and (3) intestinal dynamics that make difficult the visualization of the small intestine physiological phenomena, the analysis of the WCE data requires computer-aided systems to speed up the analysis. In this paper, we propose an efficient algorithm for building a novel representation of the WCE video data, optimal for motility analysis and inspection. The algorithm transforms the 3D video data into 2D longitudinal view by choosing the most informative, from the intestinal motility point of view, part of each frame. This step maximizes the lumen visibility in its longitudinal extension. The task of finding “the best longitudinal view” has been defined as a cost function optimization problem which global minimum is obtained by using Dynamic Programming. Validation on both synthetic data and WCE data shows that the adaptive longitudinal view is a good alternative to the traditional motility analysis done by video analysis. The proposed novel data representation a new, holistic insight into the small intestine motility, allowing to easily define and analyze motility events that are difficult to spot by analyzing WCE video. Moreover, the visual inspection of small intestine motility is 4 times faster then by means of video skimming of the WCE. |
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| Notes |
MILAB; OR; 600.046; 605.203 |
Approved |
no |
| Call Number |
Admin @ si @ DSM2012 |
Serial |
2151 |
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| Author |
Naila Murray; Maria Vanrell; Xavier Otazu; C. Alejandro Parraga |
| Title |
Low-level SpatioChromatic Grouping for Saliency Estimation |
Type |
Journal Article |
| Year |
2013 |
Publication |
IEEE Transactions on Pattern Analysis and Machine Intelligence |
Abbreviated Journal |
TPAMI |
| Volume |
35 |
Issue |
11 |
Pages |
2810-2816 |
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| Abstract |
We propose a saliency model termed SIM (saliency by induction mechanisms), which is based on a low-level spatiochromatic model that has successfully predicted chromatic induction phenomena. In so doing, we hypothesize that the low-level visual mechanisms that enhance or suppress image detail are also responsible for making some image regions more salient. Moreover, SIM adds geometrical grouplets to enhance complex low-level features such as corners, and suppress relatively simpler features such as edges. Since our model has been fitted on psychophysical chromatic induction data, it is largely nonparametric. SIM outperforms state-of-the-art methods in predicting eye fixations on two datasets and using two metrics. |
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0162-8828 |
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| Notes |
CIC; 600.051; 600.052; 605.203 |
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no |
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Admin @ si @ MVO2013 |
Serial |
2289 |
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| Author |
Mariella Dimiccoli; Benoît Girard; Alain Berthoz; Daniel Bennequin |
| Title |
Striola Magica: a functional explanation of otolith organs |
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Journal Article |
| Year |
2013 |
Publication |
Journal of Computational Neuroscience |
Abbreviated Journal |
JCN |
| Volume |
35 |
Issue |
2 |
Pages |
125-154 |
| Keywords |
Otolith organs ;Striola; Vestibular pathway |
| Abstract |
Otolith end organs of vertebrates sense linear accelerations of the head and gravitation. The hair cells on their epithelia are responsible for transduction. In mammals, the striola, parallel to the line where hair cells reverse their polarization, is a narrow region centered on a curve with curvature and torsion. It has been shown that the striolar region is functionally different from the rest, being involved in a phasic vestibular pathway. We propose a mathematical and computational model that explains the necessity of this amazing geometry for the striola to be able to carry out its function. Our hypothesis, related to the biophysics of the hair cells and to the physiology of their afferent neurons, is that striolar afferents collect information from several type I hair cells to detect the jerk in a large domain of acceleration directions. This predicts a mean number of two calyces for afferent neurons, as measured in rodents. The domain of acceleration directions sensed by our striolar model is compatible with the experimental results obtained on monkeys considering all afferents. Therefore, the main result of our study is that phasic and tonic vestibular afferents cover the same geometrical fields, but at different dynamical and frequency domains. |
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Springer US |
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1573-6873. 2013 |
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MILAB |
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no |
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Admin @ si @DBG2013 |
Serial |
2787 |
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| Author |
Albert Clapes; Miguel Reyes; Sergio Escalera |
| Title |
Multi-modal User Identification and Object Recognition Surveillance System |
Type |
Journal Article |
| Year |
2013 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
| Volume |
34 |
Issue |
7 |
Pages |
799-808 |
| Keywords |
Multi-modal RGB-Depth data analysis; User identification; Object recognition; Intelligent surveillance; Visual features; Statistical learning |
| Abstract |
We propose an automatic surveillance system for user identification and object recognition based on multi-modal RGB-Depth data analysis. We model a RGBD environment learning a pixel-based background Gaussian distribution. Then, user and object candidate regions are detected and recognized using robust statistical approaches. The system robustly recognizes users and updates the system in an online way, identifying and detecting new actors in the scene. Moreover, segmented objects are described, matched, recognized, and updated online using view-point 3D descriptions, being robust to partial occlusions and local 3D viewpoint rotations. Finally, the system saves the historic of user–object assignments, being specially useful for surveillance scenarios. The system has been evaluated on a novel data set containing different indoor/outdoor scenarios, objects, and users, showing accurate recognition and better performance than standard state-of-the-art approaches. |
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Elsevier |
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HUPBA; 600.046; 605.203;MILAB |
Approved |
no |
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Admin @ si @ CRE2013 |
Serial |
2248 |
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| Author |
Fernando Barrera; Felipe Lumbreras; Angel Sappa |
| Title |
Multispectral Piecewise Planar Stereo using Manhattan-World Assumption |
Type |
Journal Article |
| Year |
2013 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
| Volume |
34 |
Issue |
1 |
Pages |
52-61 |
| Keywords |
Multispectral stereo rig; Dense disparity maps from multispectral stereo; Color and infrared images |
| Abstract |
This paper proposes a new framework for extracting dense disparity maps from a multispectral stereo rig. The system is constructed with an infrared and a color camera. It is intended to explore novel multispectral stereo matching approaches that will allow further extraction of semantic information. The proposed framework consists of three stages. Firstly, an initial sparse disparity map is generated by using a cost function based on feature matching in a multiresolution scheme. Then, by looking at the color image, a set of planar hypotheses is defined to describe the surfaces on the scene. Finally, the previous stages are combined by reformulating the disparity computation as a global minimization problem. The paper has two main contributions. The first contribution combines mutual information with a shape descriptor based on gradient in a multiresolution scheme. The second contribution, which is based on the Manhattan-world assumption, extracts a dense disparity representation using the graph cut algorithm. Experimental results in outdoor scenarios are provided showing the validity of the proposed framework. |
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ADAS; 600.054; 600.055; 605.203 |
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Admin @ si @ BLS2013 |
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2245 |
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S.Grau; Ana Puig; Sergio Escalera; Maria Salamo |
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Intelligent Interactive Volume Classification |
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2013 |
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Pacific Graphics |
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32 |
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7 |
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23-28 |
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This paper defines an intelligent and interactive framework to classify multiple regions of interest from the original data on demand, without requiring any preprocessing or previous segmentation. The proposed intelligent and interactive approach is divided in three stages: visualize, training and testing. First, users visualize and label some samples directly on slices of the volume. Training and testing are based on a framework of Error Correcting Output Codes and Adaboost classifiers that learn to classify each region the user has painted. Later, at the testing stage, each classifier is directly applied on the rest of samples and combined to perform multi-class labeling, being used in the final rendering. We also parallelized the training stage using a GPU-based implementation for
obtaining a rapid interaction and classification. |
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978-3-905674-50-7 |
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HuPBA; 600.046;MILAB |
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Admin @ si @ GPE2013b |
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2355 |
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