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| Author | Miguel Angel Bautista; Sergio Escalera; Oriol Pujol | ||||
| Title | On the Design of an ECOC-Compliant Genetic Algorithm | Type | Journal Article | ||
| Year | 2014 | Publication | Pattern Recognition | Abbreviated Journal | PR |
| Volume | 47 | Issue | 2 | Pages | 865-884 |
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| Abstract | Genetic Algorithms (GA) have been previously applied to Error-Correcting Output Codes (ECOC) in state-of-the-art works in order to find a suitable coding matrix. Nevertheless, none of the presented techniques directly take into account the properties of the ECOC matrix. As a result the considered search space is unnecessarily large. In this paper, a novel Genetic strategy to optimize the ECOC coding step is presented. This novel strategy redefines the usual crossover and mutation operators in order to take into account the theoretical properties of the ECOC framework. Thus, it reduces the search space and lets the algorithm to converge faster. In addition, a novel operator that is able to enlarge the code in a smart way is introduced. The novel methodology is tested on several UCI datasets and four challenging computer vision problems. Furthermore, the analysis of the results done in terms of performance, code length and number of Support Vectors shows that the optimization process is able to find very efficient codes, in terms of the trade-off between classification performance and the number of classifiers. Finally, classification performance per dichotomizer results shows that the novel proposal is able to obtain similar or even better results while defining a more compact number of dichotomies and SVs compared to state-of-the-art approaches. | ||||
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| Notes | HuPBA;MILAB | Approved | no | ||
| Call Number | Admin @ si @ BEP2013 | Serial | 2254 | ||
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| Author | Vitaliy Konovalov; Albert Clapes; Sergio Escalera | ||||
| Title | Automatic Hand Detection in RGB-Depth Data Sequences | Type | Conference Article | ||
| Year | 2013 | Publication | 16th Catalan Conference on Artificial Intelligence | Abbreviated Journal | |
| Volume | Issue | Pages | 91-100 | ||
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| Abstract | Detecting hands in multi-modal RGB-Depth visual data has become a challenging Computer Vision problem with several applications of interest. This task involves dealing with changes in illumination, viewpoint variations, the articulated nature of the human body, the high flexibility of the wrist articulation, and the deformability of the hand itself. In this work, we propose an accurate and efficient automatic hand detection scheme to be applied in Human-Computer Interaction (HCI) applications in which the user is seated at the desk and, thus, only the upper body is visible. Our main hypothesis is that hand landmarks remain at a nearly constant geodesic distance from an automatically located anatomical reference point.
In a given frame, the human body is segmented first in the depth image. Then, a graph representation of the body is built in which the geodesic paths are computed from the reference point. The dense optical flow vectors on the corresponding RGB image are used to reduce ambiguities of the geodesic paths’ connectivity, allowing to eliminate false edges interconnecting different body parts. Finally, we are able to detect the position of both hands based on invariant geodesic distances and optical flow within the body region, without involving costly learning procedures. |
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| Address | Vic; October 2013 | ||||
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| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
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| Area | Expedition | Conference | CCIA | ||
| Notes | HuPBA;MILAB | Approved | no | ||
| Call Number | Admin @ si @ KCE2013 | Serial | 2323 | ||
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| Author | Miguel Reyes; Albert Clapes; Jose Ramirez; Juan R Revilla; Sergio Escalera | ||||
| Title | Automatic Digital Biometry Analysis based on Depth Maps | Type | Journal Article | ||
| Year | 2013 | Publication | Computers in Industry | Abbreviated Journal | COMPUTIND |
| Volume | 64 | Issue | 9 | Pages | 1316-1325 |
| Keywords | Multi-modal data fusion; Depth maps; Posture analysis; Anthropometric data; Musculo-skeletal disorders; Gesture analysis | ||||
| Abstract | World Health Organization estimates that 80% of the world population is affected by back-related disorders during his life. Current practices to analyze musculo-skeletal disorders (MSDs) are expensive, subjective, and invasive. In this work, we propose a tool for static body posture analysis and dynamic range of movement estimation of the skeleton joints based on 3D anthropometric information from multi-modal data. Given a set of keypoints, RGB and depth data are aligned, depth surface is reconstructed, keypoints are matched, and accurate measurements about posture and spinal curvature are computed. Given a set of joints, range of movement measurements is also obtained. Moreover, gesture recognition based on joint movements is performed to look for the correctness in the development of physical exercises. The system shows high precision and reliable measurements, being useful for posture reeducation purposes to prevent MSDs, as well as tracking the posture evolution of patients in rehabilitation treatments. | ||||
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| Publisher | Elsevier | Place of Publication | Editor | ||
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| Notes | HuPBA;MILAB | Approved | no | ||
| Call Number | Admin @ si @ RCR2013 | Serial | 2252 | ||
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| Author | Eloi Puertas; Sergio Escalera; Oriol Pujol | ||||
| Title | Generalized Multi-scale Stacked Sequential Learning for Multi-class Classification | Type | Journal Article | ||
| Year | 2015 | Publication | Pattern Analysis and Applications | Abbreviated Journal | PAA |
| Volume | 18 | Issue | 2 | Pages | 247-261 |
| Keywords | Stacked sequential learning; Multi-scale; Error-correct output codes (ECOC); Contextual classification | ||||
| Abstract | In many classification problems, neighbor data labels have inherent sequential relationships. Sequential learning algorithms take benefit of these relationships in order to improve generalization. In this paper, we revise the multi-scale sequential learning approach (MSSL) for applying it in the multi-class case (MMSSL). We introduce the error-correcting output codesframework in the MSSL classifiers and propose a formulation for calculating confidence maps from the margins of the base classifiers. In addition, we propose a MMSSL compression approach which reduces the number of features in the extended data set without a loss in performance. The proposed methods are tested on several databases, showing significant performance improvement compared to classical approaches. | ||||
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| Publisher | Springer-Verlag | Place of Publication | Editor | ||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1433-7541 | ISBN |
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| Notes | HuPBA;MILAB | Approved | no | ||
| Call Number | Admin @ si @ PEP2013 | Serial | 2251 | ||
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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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| Publisher | Elsevier | Place of Publication | Editor | ||
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| Notes | HUPBA; 600.046; 605.203;MILAB | Approved | no | ||
| Call Number | Admin @ si @ CRE2013 | Serial | 2248 | ||
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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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| Publisher | Elsevier | Place of Publication | Editor | ||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 0031-3203 | ISBN |
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| Notes | HuPBA;MILAB | Approved | no | ||
| Call Number | Admin @ si @ BGE2013a | Serial | 2247 | ||
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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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| Notes | ADAS; 600.054; 600.055; 605.203 | Approved | no | ||
| Call Number | Admin @ si @ BLS2013 | Serial | 2245 | ||
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| Author | Naveen Onkarappa; Angel Sappa | ||||
| Title | A Novel Space Variant Image Representation | Type | Journal Article | ||
| Year | 2013 | Publication | Journal of Mathematical Imaging and Vision | Abbreviated Journal | JMIV |
| Volume | 47 | Issue | 1-2 | Pages | 48-59 |
| Keywords | Space-variant representation; Log-polar mapping; Onboard vision applications | ||||
| Abstract | Traditionally, in machine vision images are represented using cartesian coordinates with uniform sampling along the axes. On the contrary, biological vision systems represent images using polar coordinates with non-uniform sampling. For various advantages provided by space-variant representations many researchers are interested in space-variant computer vision. In this direction the current work proposes a novel and simple space variant representation of images. The proposed representation is compared with the classical log-polar mapping. The log-polar representation is motivated by biological vision having the characteristic of higher resolution at the fovea and reduced resolution at the periphery. On the contrary to the log-polar, the proposed new representation has higher resolution at the periphery and lower resolution at the fovea. Our proposal is proved to be a better representation in navigational scenarios such as driver assistance systems and robotics. The experimental results involve analysis of optical flow fields computed on both proposed and log-polar representations. Additionally, an egomotion estimation application is also shown as an illustrative example. The experimental analysis comprises results from synthetic as well as real sequences. | ||||
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| Publisher | Springer US | Place of Publication | Editor | ||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 0924-9907 | ISBN |
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| Notes | ADAS; 600.055; 605.203; 601.215 | Approved | no | ||
| Call Number | Admin @ si @ OnS2013a | Serial | 2243 | ||
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| Author | Olivier Penacchio; Xavier Otazu; Laura Dempere-Marco | ||||
| Title | A Neurodynamical Model of Brightness Induction in V1 | Type | Journal Article | ||
| Year | 2013 | Publication | PloS ONE | Abbreviated Journal | Plos |
| Volume | 8 | Issue | 5 | Pages | e64086 |
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| Abstract | Brightness induction is the modulation of the perceived intensity of an area by the luminance of surrounding areas. Recent neurophysiological evidence suggests that brightness information might be explicitly represented in V1, in contrast to the more common assumption that the striate cortex is an area mostly responsive to sensory information. Here we investigate possible neural mechanisms that offer a plausible explanation for such phenomenon. To this end, a neurodynamical model which is based on neurophysiological evidence and focuses on the part of V1 responsible for contextual influences is presented. The proposed computational model successfully accounts for well known psychophysical effects for static contexts and also for brightness induction in dynamic contexts defined by modulating the luminance of surrounding areas. This work suggests that intra-cortical interactions in V1 could, at least partially, explain brightness induction effects and reveals how a common general architecture may account for several different fundamental processes, such as visual saliency and brightness induction, which emerge early in the visual processing pathway. | ||||
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| Notes | CIC | Approved | no | ||
| Call Number | Admin @ si @ POD2013 | Serial | 2242 | ||
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| Author | Naveen Onkarappa; Angel Sappa | ||||
| Title | Speed and Texture: An Empirical Study on Optical-Flow Accuracy in ADAS Scenarios | Type | Journal Article | ||
| Year | 2014 | Publication | IEEE Transactions on Intelligent Transportation Systems | Abbreviated Journal | TITS |
| Volume | 15 | Issue | 1 | Pages | 136-147 |
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| Abstract | IF: 3.064
Increasing mobility in everyday life has led to the concern for the safety of automotives and human life. Computer vision has become a valuable tool for developing driver assistance applications that target such a concern. Many such vision-based assisting systems rely on motion estimation, where optical flow has shown its potential. A variational formulation of optical flow that achieves a dense flow field involves a data term and regularization terms. Depending on the image sequence, the regularization has to appropriately be weighted for better accuracy of the flow field. Because a vehicle can be driven in different kinds of environments, roads, and speeds, optical-flow estimation has to be accurately computed in all such scenarios. In this paper, we first present the polar representation of optical flow, which is quite suitable for driving scenarios due to the possibility that it offers to independently update regularization factors in different directional components. Then, we study the influence of vehicle speed and scene texture on optical-flow accuracy. Furthermore, we analyze the relationships of these specific characteristics on a driving scenario (vehicle speed and road texture) with the regularization weights in optical flow for better accuracy. As required by the work in this paper, we have generated several synthetic sequences along with ground-truth flow fields. |
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| ISSN | 1524-9050 | ISBN |
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| Notes | ADAS; 600.076 | Approved | no | ||
| Call Number | Admin @ si @ OnS2014a | Serial | 2386 | ||
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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 | |
| 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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| ISSN | 1520-5363 | ISBN |
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| 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 | |
| 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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| 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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| Area | Expedition | Conference | MVA | ||
| Notes | OR; MILAB;MV | Approved | no | ||
| Call Number | BVR2013 | Serial | 2238 | ||
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