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Records |
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Author |
Fahad Shahbaz Khan; Joost Van de Weijer; Sadiq Ali; Michael Felsberg |
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Title |
Evaluating the impact of color on texture recognition |
Type |
Conference Article |
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Year |
2013 |
Publication |
15th International Conference on Computer Analysis of Images and Patterns |
Abbreviated Journal |
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Volume |
8047 |
Issue |
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Pages |
154-162 |
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Keywords |
Color; Texture; image representation |
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Abstract |
State-of-the-art texture descriptors typically operate on grey scale images while ignoring color information. A common way to obtain a joint color-texture representation is to combine the two visual cues at the pixel level. However, such an approach provides sub-optimal results for texture categorisation task.
In this paper we investigate how to optimally exploit color information for texture recognition. We evaluate a variety of color descriptors, popular in image classification, for texture categorisation. In addition we analyze different fusion approaches to combine color and texture cues. Experiments are conducted on the challenging scenes and 10 class texture datasets. Our experiments clearly suggest that in all cases color names provide the best performance. Late fusion is the best strategy to combine color and texture. By selecting the best color descriptor with optimal fusion strategy provides a gain of 5% to 8% compared to texture alone on scenes and texture datasets. |
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Address |
York; UK; August 2013 |
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Springer Berlin Heidelberg |
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ISSN |
0302-9743 |
ISBN |
978-3-642-40260-9 |
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CAIP |
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Notes |
CIC; 600.048 |
Approved |
no |
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Call Number |
Admin @ si @ KWA2013 |
Serial |
2263 |
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Permanent link to this record |
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Author |
Francesco Ciompi; Simone Balocco; Carles Caus; J. Mauri; Petia Radeva |
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Title |
Stent shape estimation through a comprehensive interpretation of intravascular ultrasound images |
Type |
Conference Article |
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Year |
2013 |
Publication |
16th International Conference on Medical Image Computing and Computer Assisted Intervention |
Abbreviated Journal |
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Volume |
8150 |
Issue |
2 |
Pages |
345-352 |
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Abstract |
We present a method for automatic struts detection and stent shape estimation in cross-sectional intravascular ultrasound images. A stent shape is first estimated through a comprehensive interpretation of the vessel morphology, performed using a supervised context-aware multi-class classification scheme. Then, the successive strut identification exploits both local appearance and the defined stent shape. The method is tested on 589 images obtained from 80 patients, achieving a F-measure of 74.1% and an averaged distance between manual and automatic struts of 0.10 mm. |
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Address |
Nagoya; Japan; September 2013 |
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Publisher |
Springer Berlin Heidelberg |
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ISSN |
0302-9743 |
ISBN |
978-3-642-40762-8 |
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Conference |
MICCAI |
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Notes |
MILAB |
Approved |
no |
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Call Number |
Admin @ si @ CBC2013 |
Serial |
2258 |
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Permanent link to this record |
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Author |
Daniel Sanchez; J.C.Ortega; Miguel Angel Bautista |
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Title |
Human Body Segmentation with Multi-limb Error-Correcting Output Codes Detection and Graph Cuts Optimization |
Type |
Conference Article |
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Year |
2013 |
Publication |
6th Iberian Conference on Pattern Recognition and Image Analysis |
Abbreviated Journal |
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Volume |
7887 |
Issue |
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Pages |
50-58 |
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Keywords |
Human Body Segmentation; Error-Correcting Output Codes; Cascade of Classifiers; Graph Cuts |
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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. |
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Address |
Madeira; Portugal; June 2013 |
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Springer Berlin Heidelberg |
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LNCS |
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Edition |
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ISSN |
0302-9743 |
ISBN |
978-3-642-38627-5 |
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Conference |
IbPRIA |
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Notes |
HUPBA |
Approved |
no |
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Call Number |
SOB2013 |
Serial |
2250 |
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Permanent link to this record |
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Author |
Mohammad Ali Bagheri; Qigang Gao; Sergio Escalera |
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Title |
Logo recognition Based on the Dempster-Shafer Fusion of Multiple Classifiers |
Type |
Conference Article |
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Year |
2013 |
Publication |
26th Canadian Conference on Artificial Intelligence |
Abbreviated Journal |
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Volume |
7884 |
Issue |
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Pages |
1-12 |
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Keywords |
Logo recognition; ensemble classification; Dempster-Shafer fusion; Zernike moments; generic Fourier descriptor; shape signature |
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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 |
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Publisher |
Springer Berlin Heidelberg |
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ISSN |
0302-9743 |
ISBN |
978-3-642-38456-1 |
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Expedition |
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Conference |
AI |
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Notes |
HuPBA;MILAB |
Approved |
no |
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Call Number |
Admin @ si @ BGE2013b |
Serial |
2249 |
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Permanent link to this record |
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Author |
Naveen Onkarappa; Angel Sappa |
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Title |
Laplacian Derivative based Regularization for Optical Flow Estimation in Driving Scenario |
Type |
Conference Article |
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Year |
2013 |
Publication |
15th International Conference on Computer Analysis of Images and Patterns |
Abbreviated Journal |
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Volume |
8048 |
Issue |
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Pages |
483-490 |
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Keywords |
Optical flow; regularization; Driver Assistance Systems; Performance Evaluation |
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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). |
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Address |
York; UK; August 2013 |
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Publisher |
Springer Berlin Heidelberg |
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LNCS |
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Series Volume |
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Edition |
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ISSN |
0302-9743 |
ISBN |
978-3-642-40245-6 |
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Conference |
CAIP |
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Notes |
ADAS; 600.055; 601.215 |
Approved |
no |
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Call Number |
Admin @ si @ OnS2013b |
Serial |
2244 |
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Permanent link to this record |
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Author |
Michal Drozdzal; Santiago Segui; Petia Radeva; Carolina Malagelada; Fernando Azpiroz; Jordi Vitria |
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Title |
An Application for Efficient Error-Free Labeling of Medical Images |
Type |
Book Chapter |
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Year |
2013 |
Publication |
Multimodal Interaction in Image and Video Applications |
Abbreviated Journal |
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Volume |
48 |
Issue |
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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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Corporate Author |
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Publisher |
Springer Berlin Heidelberg |
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Series Editor |
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Edition |
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ISSN |
1868-4394 |
ISBN |
978-3-642-35931-6 |
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Notes |
MILAB; OR;MV |
Approved |
no |
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Call Number |
Admin @ si @ DSR2013 |
Serial |
2235 |
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Permanent link to this record |
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Author |
Ariel Amato; Ivan Huerta; Mikhail Mozerov; Xavier Roca; Jordi Gonzalez |
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Title |
Moving Cast Shadows Detection Methods for Video Surveillance Applications |
Type |
Book Chapter |
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Year |
2014 |
Publication |
Augmented Vision and Reality |
Abbreviated Journal |
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Volume |
6 |
Issue |
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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 |
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ISSN |
2190-5916 |
ISBN |
978-3-642-37840-9 |
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Notes |
ISE; 605.203; 600.049; 302.018; 302.012; 600.078 |
Approved |
no |
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Call Number |
Admin @ si @ AHM2014 |
Serial |
2223 |
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Permanent link to this record |
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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 |
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Title |
Exploiting Multimodal Interaction Techniques for Video-Surveillance |
Type |
Book Chapter |
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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 |
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ISSN |
1868-4394 |
ISBN |
978-3-642-35931-6 |
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Notes |
ISE; 605.203; 600.049 |
Approved |
no |
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Call Number |
CGA2013 |
Serial |
2222 |
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Permanent link to this record |
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Author |
Miguel Angel Bautista; Antonio Hernandez; Victor Ponce; Xavier Perez Sala; Xavier Baro; Oriol Pujol; Cecilio Angulo; Sergio Escalera |
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Title |
Probability-based Dynamic TimeWarping for Gesture Recognition on RGB-D data |
Type |
Conference Article |
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Year |
2012 |
Publication |
21st International Conference on Pattern Recognition International Workshop on Depth Image Analysis |
Abbreviated Journal |
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Volume |
7854 |
Issue |
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Pages |
126-135 |
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Keywords |
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Abstract |
Dynamic Time Warping (DTW) is commonly used in gesture recognition tasks in order to tackle the temporal length variability of gestures. In the DTW framework, a set of gesture patterns are compared one by one to a maybe infinite test sequence, and a query gesture category is recognized if a warping cost below a certain threshold is found within the test sequence. Nevertheless, either taking one single sample per gesture category or a set of isolated samples may not encode the variability of such gesture category. In this paper, a probability-based DTW for gesture recognition is proposed. Different samples of the same gesture pattern obtained from RGB-Depth data are used to build a Gaussian-based probabilistic model of the gesture. Finally, the cost of DTW has been adapted accordingly to the new model. The proposed approach is tested in a challenging scenario, showing better performance of the probability-based DTW in comparison to state-of-the-art approaches for gesture recognition on RGB-D data. |
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Publisher |
Springer Berlin Heidelberg |
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ISSN |
0302-9743 |
ISBN |
978-3-642-40302-6 |
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Conference |
WDIA |
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Notes |
MILAB; OR;HuPBA;MV |
Approved |
no |
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Call Number |
Admin @ si @ BHP2012 |
Serial |
2120 |
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Permanent link to this record |
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Author |
Miguel Reyes; Albert Clapes; Luis Felipe Mejia; Jose Ramirez; Juan R Revilla; Sergio Escalera |
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Title |
Posture Analysis and Range of Movement Estimation using Depth Maps |
Type |
Conference Article |
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Year |
2012 |
Publication |
21st International Conference on Pattern Recognition International Workshop on Depth Image Analysis |
Abbreviated Journal |
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Volume |
7854 |
Issue |
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Pages |
97-105 |
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Keywords |
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Abstract |
World Health Organization estimates that 80% of the world population is affected of back pain during his life. Current practices to analyze back problems are expensive, subjective, and invasive. In this work, we propose a novel tool for posture and range of movement estimation based on the analysis of 3D information from depth maps. Given a set of keypoints defined by the user, RGB and depth data are aligned, depth surface is reconstructed, keypoints are matching using a novel point-to-point fitting procedure, and accurate measurements about posture, spinal curvature, and range of movement are computed. The system shows high precision and reliable measurements, being useful for posture reeducation purposes to prevent musculoskeletal disorders, such as back pain, as well as tracking the posture evolution of patients in rehabilitation treatments. |
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Springer Berlin Heidelberg |
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ISSN |
0302-9743 |
ISBN |
978-3-642-40302-6 |
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Expedition |
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Conference |
WDIA |
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Notes |
HuPBA;MILAB |
Approved |
no |
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Call Number |
Admin @ si @ RCM2012 |
Serial |
2121 |
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Permanent link to this record |
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Author |
Klaus Broelemann; Anjan Dutta; Xiaoyi Jiang; Josep Llados |
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Title |
Hierarchical graph representation for symbol spotting in graphical document images |
Type |
Conference Article |
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Year |
2012 |
Publication |
Structural, Syntactic, and Statistical Pattern Recognition, Joint IAPR International Workshop |
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Volume |
7626 |
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Pages |
529-538 |
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Abstract |
Symbol spotting can be defined as locating given query symbol in a large collection of graphical documents. In this paper we present a hierarchical graph representation for symbols. This representation allows graph matching methods to deal with low-level vectorization errors and, thus, to perform a robust symbol spotting. To show the potential of this approach, we conduct an experiment with the SESYD dataset. |
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Address |
Miyajima-Itsukushima, Hiroshima |
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Publisher |
Springer Berlin Heidelberg |
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LNCS |
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ISSN |
0302-9743 |
ISBN |
978-3-642-34165-6 |
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Conference |
SSPR&SPR |
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Notes |
DAG |
Approved |
no |
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Call Number |
Admin @ si @ BDJ2012 |
Serial |
2126 |
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Permanent link to this record |
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Author |
David Masip; Alexander Todorov; Jordi Vitria |
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Title |
The Role of Facial Regions in Evaluating Social Dime |
Type |
Conference Article |
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Year |
2012 |
Publication |
12th European Conference on Computer Vision – Workshops and Demonstrations |
Abbreviated Journal |
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Volume |
7584 |
Issue |
II |
Pages |
210-219 |
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Keywords |
Workshops and Demonstrations |
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Abstract |
Facial trait judgments are an important information cue for people. Recent works in the Psychology field have stated the basis of face evaluation, defining a set of traits that we evaluate from faces (e.g. dominance, trustworthiness, aggressiveness, attractiveness, threatening or intelligence among others). We rapidly infer information from others faces, usually after a short period of time (< 1000ms) we perceive a certain degree of dominance or trustworthiness of another person from the face. Although these perceptions are not necessarily accurate, they influence many important social outcomes (such as the results of the elections or the court decisions). This topic has also attracted the attention of Computer Vision scientists, and recently a computational model to automatically predict trait evaluations from faces has been proposed. These systems try to mimic the human perception by means of applying machine learning classifiers to a set of labeled data. In this paper we perform an experimental study on the specific facial features that trigger the social inferences. Using previous results from the literature, we propose to use simple similarity maps to evaluate which regions of the face influence the most the trait inferences. The correlation analysis is performed using only appearance, and the results from the experiments suggest that each trait is correlated with specific facial characteristics. |
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Address |
Florence, Italy |
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Springer Berlin Heidelberg |
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Editor |
Andrea Fusiello, Vittorio Murino, Rita Cucchiara |
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LNCS |
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ISSN |
0302-9743 |
ISBN |
978-3-642-33867-0 |
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Conference |
ECCVW |
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Notes |
OR;MV |
Approved |
no |
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Call Number |
Admin @ si @ MTV2012 |
Serial |
2171 |
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Permanent link to this record |
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Author |
Karel Paleček; David Geronimo; Frederic Lerasle |
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Title |
Pre-attention cues for person detection |
Type |
Conference Article |
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Year |
2012 |
Publication |
Cognitive Behavioural Systems, COST 2102 International Training School |
Abbreviated Journal |
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Volume |
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Issue |
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Pages |
225-235 |
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Abstract |
Current state-of-the-art person detectors have been proven reliable and achieve very good detection rates. However, the performance is often far from real time, which limits their use to low resolution images only. In this paper, we deal with candidate window generation problem for person detection, i.e. we want to reduce the computational complexity of a person detector by reducing the number of regions that has to be evaluated. We base our work on Alexe’s paper [1], which introduced several pre-attention cues for generic object detection. We evaluate these cues in the context of person detection and show that their performance degrades rapidly for scenes containing multiple objects of interest such as pictures from urban environment. We extend this set by new cues, which better suits our class-specific task. The cues are designed to be simple and efficient, so that they can be used in the pre-attention phase of a more complex sliding window based person detector. |
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Address |
Dresden, Germany |
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Thesis |
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Publisher |
Springer Berlin Heidelberg |
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Original Title |
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Abbreviated Series Title |
LNCS |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
0302-9743 |
ISBN |
978-3-642-34583-8 |
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Expedition |
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Conference |
COST-TS |
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Notes |
ADAS |
Approved |
no |
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Call Number |
Admin @ si @ PGL2012 |
Serial |
2148 |
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Permanent link to this record |
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Author |
Jose Carlos Rubio; Joan Serrat; Antonio Lopez |
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Title |
Video Co-segmentation |
Type |
Conference Article |
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Year |
2012 |
Publication |
11th Asian Conference on Computer Vision |
Abbreviated Journal |
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Volume |
7725 |
Issue |
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Pages |
13-24 |
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Keywords |
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Abstract |
Segmentation of a single image is in general a highly underconstrained problem. A frequent approach to solve it is to somehow provide prior knowledge or constraints on how the objects of interest look like (in terms of their shape, size, color, location or structure). Image co-segmentation trades the need for such knowledge for something much easier to obtain, namely, additional images showing the object from other viewpoints. Now the segmentation problem is posed as one of differentiating the similar object regions in all the images from the more varying background. In this paper, for the first time, we extend this approach to video segmentation: given two or more video sequences showing the same object (or objects belonging to the same class) moving in a similar manner, we aim to outline its region in all the frames. In addition, the method works in an unsupervised manner, by learning to segment at testing time. We compare favorably with two state-of-the-art methods on video segmentation and report results on benchmark videos. |
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Address |
Daejeon, Korea |
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Publisher |
Springer Berlin Heidelberg |
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LNCS |
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Series Volume |
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Edition |
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ISSN |
0302-9743 |
ISBN |
978-3-642-37443-2 |
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Expedition |
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Conference |
ACCV |
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Notes |
ADAS |
Approved |
no |
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Call Number |
Admin @ si @ RSL2012d |
Serial |
2153 |
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Author |
Mohammad Rouhani; Angel Sappa |
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Title |
Non-Rigid Shape Registration: A Single Linear Least Squares Framework |
Type |
Conference Article |
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Year |
2012 |
Publication |
12th European Conference on Computer Vision |
Abbreviated Journal |
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Volume |
7578 |
Issue |
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Pages |
264-277 |
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Keywords |
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Abstract |
This paper proposes a non-rigid registration formulation capturing both global and local deformations in a single framework. This formulation is based on a quadratic estimation of the registration distance together with a quadratic regularization term. Hence, the optimal transformation parameters are easily obtained by solving a liner system of equations, which guarantee a fast convergence. Experimental results with challenging 2D and 3D shapes are presented to show the validity of the proposed framework. Furthermore, comparisons with the most relevant approaches are provided. |
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Address |
Florencia |
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Thesis |
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Publisher |
Springer Berlin Heidelberg |
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LNCS |
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Edition |
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ISSN |
0302-9743 |
ISBN |
978-3-642-33785-7 |
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Expedition |
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Conference |
ECCV |
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Notes |
ADAS |
Approved |
no |
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Call Number |
Admin @ si @ RoS2012a |
Serial |
2158 |
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Permanent link to this record |