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| Author | Adriana Romero; Carlo Gatta | ||||
| Title | Do We Really Need All These Neurons? | Type | Conference Article | ||
| Year | 2013 | Publication | 6th Iberian Conference on Pattern Recognition and Image Analysis | Abbreviated Journal | |
| Volume | 7887 | Issue | Pages | 460--467 | |
Keywords  |
Retricted Boltzmann Machine; hidden units; unsupervised learning; classification | ||||
| Abstract | Restricted Boltzmann Machines (RBMs) are generative neural networks that have received much attention recently. In particular, choosing the appropriate number of hidden units is important as it might hinder their representative power. According to the literature, RBM require numerous hidden units to approximate any distribution properly. In this paper, we present an experiment to determine whether such amount of hidden units is required in a classification context. We then propose an incremental algorithm that trains RBM reusing the previously trained parameters using a trade-off measure to determine the appropriate number of hidden units. Results on the MNIST and OCR letters databases show that using a number of hidden units, which is one order of magnitude smaller than the literature estimate, suffices to achieve similar performance. Moreover, the proposed algorithm allows to estimate the required number of hidden units without the need of training many RBM from scratch. | ||||
| 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 | MILAB; 600.046 | Approved | no | ||
| Call Number | Admin @ si @ RoG2013 | Serial | 2311 | ||
| Permanent link to this record | |||||
| Author | Jiaolong Xu; David Vazquez; Antonio Lopez; Javier Marin; Daniel Ponsa | ||||
| Title | Learning a Multiview Part-based Model in Virtual World for Pedestrian Detection | Type | Conference Article | ||
| Year | 2013 | Publication | IEEE Intelligent Vehicles Symposium | Abbreviated Journal | |
| Volume | Issue | Pages | 467 - 472 | ||
| Keywords |
Pedestrian Detection; Virtual World; Part based | ||||
| Abstract | State-of-the-art deformable part-based models based on latent SVM have shown excellent results on human detection. In this paper, we propose to train a multiview deformable part-based model with automatically generated part examples from virtual-world data. The method is efficient as: (i) the part detectors are trained with precisely extracted virtual examples, thus no latent learning is needed, (ii) the multiview pedestrian detector enhances the performance of the pedestrian root model, (iii) a top-down approach is used for part detection which reduces the searching space. We evaluate our model on Daimler and Karlsruhe Pedestrian Benchmarks with publicly available Caltech pedestrian detection evaluation framework and the result outperforms the state-of-the-art latent SVM V4.0, on both average miss rate and speed (our detector is ten times faster). | ||||
| Address | Gold Coast; Australia; June 2013 | ||||
| Corporate Author | Thesis | ||||
| Publisher | IEEE | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 1931-0587 | ISBN | 978-1-4673-2754-1 | Medium | |
| Area | Expedition | Conference | IV | ||
| Notes | ADAS; 600.054; 600.057 | Approved | no | ||
| Call Number | XVL2013; ADAS @ adas @ xvl2013a | Serial | 2214 | ||
| Permanent link to this record | |||||
| Author | David Vazquez; Antonio Lopez; Daniel Ponsa; David Geronimo | ||||
| Title | Interactive Training of Human Detectors | Type | Book Chapter | ||
| Year | 2013 | Publication | Multiodal Interaction in Image and Video Applications | Abbreviated Journal | |
| Volume | 48 | Issue | Pages | 169-182 | |
| Keywords |
Pedestrian Detection; Virtual World; AdaBoost; Domain Adaptation | ||||
| Abstract | Image based human detection remains as a challenging problem. Most promising detectors rely on classifiers trained with labelled samples. However, labelling is a manual labor intensive step. To overcome this problem we propose to collect images of pedestrians from a virtual city, i.e., with automatic labels, and train a pedestrian detector with them, which works fine when such virtual-world data are similar to testing one, i.e., real-world pedestrians in urban areas. When testing data is acquired in different conditions than training one, e.g., human detection in personal photo albums, dataset shift appears. In previous work, we cast this problem as one of domain adaptation and solve it with an active learning procedure. In this work, we focus on the same problem but evaluating a different set of faster to compute features, i.e., Haar, EOH and their combination. In particular, we train a classifier with virtual-world data, using such features and Real AdaBoost as learning machine. This classifier is applied to real-world training images. Then, a human oracle interactively corrects the wrong detections, i.e., few miss detections are manually annotated and some false ones are pointed out too. A low amount of manual annotation is fixed as restriction. Real- and virtual-world difficult samples are combined within what we call cool world and we retrain the classifier with this data. Our experiments show that this adapted classifier is equivalent to the one trained with only real-world data but requiring 90% less manual annotations. | ||||
| Address | Springer Heidelberg New York Dordrecht London | ||||
| Corporate Author | Thesis | ||||
| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
| Language | English | Summary Language | Original Title | ||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 1868-4394 | ISBN | 978-3-642-35931-6 | Medium | |
| Area | Expedition | Conference | |||
| Notes | ADAS; 600.057; 600.054; 605.203 | Approved | no | ||
| Call Number | VLP2013; ADAS @ adas @ vlp2013 | Serial | 2193 | ||
| Permanent link to this record | |||||
| Author | David Vazquez | ||||
| Title | Domain Adaptation of Virtual and Real Worlds for Pedestrian Detection | Type | Book Whole | ||
| Year | 2013 | Publication | PhD Thesis, Universitat de Barcelona-CVC | Abbreviated Journal | |
| Volume | 1 | Issue | 1 | Pages | 1-105 |
| Keywords |
Pedestrian Detection; Domain Adaptation | ||||
| Abstract | Pedestrian detection is of paramount interest for many applications, e.g. Advanced Driver Assistance Systems, Intelligent Video Surveillance and Multimedia systems. Most promising pedestrian detectors rely on appearance-based classifiers trained with annotated data. However, the required annotation step represents an intensive and subjective task for humans, what makes worth to minimize their intervention in this process by using computational tools like realistic virtual worlds. The reason to use these kind of tools relies in the fact that they allow the automatic generation of precise and rich annotations of visual information. Nevertheless, the use of this kind of data comes with the following question: can a pedestrian appearance model learnt with virtual-world data work successfully for pedestrian detection in real-world scenarios?. To answer this question, we conduct different experiments that suggest a positive answer. However, the pedestrian classifiers trained with virtual-world data can suffer the so called dataset shift problem as real-world based classifiers does. Accordingly, we have designed different domain adaptation techniques to face this problem, all of them integrated in a same framework (V-AYLA). We have explored different methods to train a domain adapted pedestrian classifiers by collecting a few pedestrian samples from the target domain (real world) and combining them with many samples of the source domain (virtual world). The extensive experiments we present show that pedestrian detectors developed within the V-AYLA framework do achieve domain adaptation. Ideally, we would like to adapt our system without any human intervention. Therefore, as a first proof of concept we also propose an unsupervised domain adaptation technique that avoids human intervention during the adaptation process. To the best of our knowledge, this Thesis work is the first demonstrating adaptation of virtual and real worlds for developing an object detector. Last but not least, we also assessed a different strategy to avoid the dataset shift that consists in collecting real-world samples and retrain with them in such a way that no bounding boxes of real-world pedestrians have to be provided. We show that the generated classifier is competitive with respect to the counterpart trained with samples collected by manually annotating pedestrian bounding boxes. The results presented on this Thesis not only end with a proposal for adapting a virtual-world pedestrian detector to the real world, but also it goes further by pointing out a new methodology that would allow the system to adapt to different situations, which we hope will provide the foundations for future research in this unexplored area. | ||||
| Address | Barcelona | ||||
| Corporate Author | Thesis | Ph.D. thesis | |||
| Publisher | Ediciones Graficas Rey | Place of Publication | Barcelona | Editor | Antonio Lopez;Daniel Ponsa |
| Language | English | Summary Language | Original Title | ||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-84-940530-1-6 | Medium | ||
| Area | Expedition | Conference | |||
| Notes | adas | Approved | yes | ||
| Call Number | ADAS @ adas @ Vaz2013 | Serial | 2276 | ||
| Permanent link to this record | |||||
| Author | David Vazquez; Jiaolong Xu; Sebastian Ramos; Antonio Lopez; Daniel Ponsa | ||||
| Title | Weakly Supervised Automatic Annotation of Pedestrian Bounding Boxes | Type | Conference Article | ||
| Year | 2013 | Publication | CVPR Workshop on Ground Truth – What is a good dataset? | Abbreviated Journal | |
| Volume | Issue | Pages | 706 - 711 | ||
| Keywords |
Pedestrian Detection; Domain Adaptation | ||||
| Abstract | Among the components of a pedestrian detector, its trained pedestrian classifier is crucial for achieving the desired performance. The initial task of the training process consists in collecting samples of pedestrians and background, which involves tiresome manual annotation of pedestrian bounding boxes (BBs). Thus, recent works have assessed the use of automatically collected samples from photo-realistic virtual worlds. However, learning from virtual-world samples and testing in real-world images may suffer the dataset shift problem. Accordingly, in this paper we assess an strategy to collect samples from the real world and retrain with them, thus avoiding the dataset shift, but in such a way that no BBs of real-world pedestrians have to be provided. In particular, we train a pedestrian classifier based on virtual-world samples (no human annotation required). Then, using such a classifier we collect pedestrian samples from real-world images by detection. After, a human oracle rejects the false detections efficiently (weak annotation). Finally, a new classifier is trained with the accepted detections. We show that this classifier is competitive with respect to the counterpart trained with samples collected by manually annotating hundreds of pedestrian BBs. | ||||
| Address | Portland; Oregon; June 2013 | ||||
| Corporate Author | Thesis | ||||
| Publisher | IEEE | Place of Publication | Editor | ||
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | Medium | |||
| Area | Expedition | Conference | CVPRW | ||
| Notes | ADAS; 600.054; 600.057; 601.217 | Approved | no | ||
| Call Number | ADAS @ adas @ VXR2013a | Serial | 2219 | ||
| Permanent link to this record | |||||
| Author | Jiaolong Xu; David Vazquez; Sebastian Ramos; Antonio Lopez; Daniel Ponsa | ||||
| Title | Adapting a Pedestrian Detector by Boosting LDA Exemplar Classifiers | Type | Conference Article | ||
| Year | 2013 | Publication | CVPR Workshop on Ground Truth – What is a good dataset? | Abbreviated Journal | |
| Volume | Issue | Pages | 688 - 693 | ||
| Keywords |
Pedestrian Detection; Domain Adaptation | ||||
| Abstract | Training vision-based pedestrian detectors using synthetic datasets (virtual world) is a useful technique to collect automatically the training examples with their pixel-wise ground truth. However, as it is often the case, these detectors must operate in real-world images, experiencing a significant drop of their performance. In fact, this effect also occurs among different real-world datasets, i.e. detectors' accuracy drops when the training data (source domain) and the application scenario (target domain) have inherent differences. Therefore, in order to avoid this problem, it is required to adapt the detector trained with synthetic data to operate in the real-world scenario. In this paper, we propose a domain adaptation approach based on boosting LDA exemplar classifiers from both virtual and real worlds. We evaluate our proposal on multiple real-world pedestrian detection datasets. The results show that our method can efficiently adapt the exemplar classifiers from virtual to real world, avoiding drops in average precision over the 15%. | ||||
| Address | Portland; oregon; June 2013 | ||||
| Corporate Author | Thesis | ||||
| Publisher | Place of Publication | Editor | |||
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | Medium | |||
| Area | Expedition | Conference | CVPRW | ||
| Notes | ADAS; 600.054; 600.057; 601.217 | Approved | yes | ||
| Call Number | XVR2013; ADAS @ adas @ xvr2013a | Serial | 2220 | ||
| Permanent link to this record | |||||
| 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. | ||||
| Address | |||||
| Corporate Author | Thesis | ||||
| Publisher | Elsevier | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0031-3203 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | DAG; 600.042; 600.045; 605.203 | Approved | no | ||
| Call Number | Admin @ si @ LRL2013a | Serial | 2270 | ||
| Permanent link to this record | |||||
| Author | R. Bertrand; P. Gomez-Krämer; Oriol Ramos Terrades; P. Franco; Jean-Marc Ogier | ||||
| Title | A System Based On Intrinsic Features for Fraudulent Document Detection | Type | Conference Article | ||
| Year | 2013 | Publication | 12th International Conference on Document Analysis and Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | 106-110 | ||
| Keywords |
paper document; document analysis; fraudulent document; forgery; fake | ||||
| Abstract | Paper documents still represent a large amount of information supports used nowadays and may contain critical data. Even though official documents are secured with techniques such as printed patterns or artwork, paper documents suffer froma lack of security.
However, the high availability of cheap scanning and printing hardware allows non-experts to easily create fake documents. As the use of a watermarking system added during the document production step is hardly possible, solutions have to be proposed to distinguish a genuine document from a forged one. In this paper, we present an automatic forgery detection method based on document’s intrinsic features at character level. This method is based on the one hand on outlier character detection in a discriminant feature space and on the other hand on the detection of strictly similar characters. Therefore, a feature set iscomputed for all characters. Then, based on a distance between characters of the same class. |
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| Address | Washington; USA; August 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 | 1520-5363 | ISBN | Medium | ||
| Area | Expedition | Conference | ICDAR | ||
| Notes | DAG; 600.061 | Approved | no | ||
| Call Number | Admin @ si @ BGR2013a | Serial | 2332 | ||
| Permanent link to this record | |||||
| Author | Mariella Dimiccoli; Benoît Girard; Alain Berthoz; Daniel Bennequin | ||||
| Title | Striola Magica: a functional explanation of otolith organs | Type | 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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| Corporate Author | Thesis | ||||
| Publisher | Springer US | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 1573-6873. 2013 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | MILAB | Approved | no | ||
| Call Number | Admin @ si @DBG2013 | Serial | 2787 | ||
| Permanent link to this record | |||||
| 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 | |
| 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 | Patricia Marquez; Debora Gil; Aura Hernandez-Sabate; Daniel Kondermann | ||||
| Title | When Is A Confidence Measure Good Enough? | Type | Conference Article | ||
| Year | 2013 | Publication | 9th International Conference on Computer Vision Systems | Abbreviated Journal | |
| Volume | 7963 | Issue | Pages | 344-353 | |
| Keywords |
Optical flow, confidence measure, performance evaluation | ||||
| Abstract | Confidence estimation has recently become a hot topic in image processing and computer vision.Yet, several definitions exist of the term “confidence” which are sometimes used interchangeably. This is a position paper, in which we aim to give an overview on existing definitions,
thereby clarifying the meaning of the used terms to facilitate further research in this field. Based on these clarifications, we develop a theory to compare confidence measures with respect to their quality. |
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| Address | St Petersburg; Russia; July 2013 | ||||
| Corporate Author | Thesis | ||||
| Publisher | Springer Link | 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 | 978-3-642-39401-0 | Medium | |
| Area | Expedition | Conference | ICVS | ||
| Notes | IAM;ADAS; 600.044; 600.057; 600.060; 601.145 | Approved | no | ||
| Call Number | IAM @ iam @ MGH2013a | Serial | 2218 | ||
| Permanent link to this record | |||||
| Author | Santiago Segui; Laura Igual; Jordi Vitria | ||||
| Title | Bagged One Class Classifiers in the Presence of Outliers | Type | Journal Article | ||
| Year | 2013 | Publication | International Journal of Pattern Recognition and Artificial Intelligence | Abbreviated Journal | IJPRAI |
| Volume | 27 | Issue | 5 | Pages | 1350014-1350035 |
| Keywords |
One-class Classifier; Ensemble Methods; Bagging and Outliers | ||||
| Abstract | The problem of training classifiers only with target data arises in many applications where non-target data are too costly, difficult to obtain, or not available at all. Several one-class classification methods have been presented to solve this problem, but most of the methods are highly sensitive to the presence of outliers in the target class. Ensemble methods have therefore been proposed as a powerful way to improve the classification performance of binary/multi-class learning algorithms by introducing diversity into classifiers.
However, their application to one-class classification has been rather limited. In this paper, we present a new ensemble method based on a non-parametric weighted bagging strategy for one-class classification, to improve accuracy in the presence of outliers. While the standard bagging strategy assumes a uniform data distribution, the method we propose here estimates a probability density based on a forest structure of the data. This assumption allows the estimation of data distribution from the computation of simple univariate and bivariate kernel densities. Experiments using original and noisy versions of 20 different datasets show that bagging ensemble methods applied to different one-class classifiers outperform base one-class classification methods. Moreover, we show that, in noisy versions of the datasets, the non-parametric weighted bagging strategy we propose outperforms the classical bagging strategy in a statistically significant way. |
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| Area | Expedition | Conference | |||
| Notes | OR; 600.046;MV | Approved | no | ||
| Call Number | Admin @ si @ SIV2013 | Serial | 2256 | ||
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| Author | Joan Serrat; Felipe Lumbreras; Antonio Lopez | ||||
| Title | Cost estimation of custom hoses from STL files and CAD drawings | Type | Journal Article | ||
| Year | 2013 | Publication | Computers in Industry | Abbreviated Journal | COMPUTIND |
| Volume | 64 | Issue | 3 | Pages | 299-309 |
| Keywords |
On-line quotation; STL format; Regression; Gaussian process | ||||
| Abstract | We present a method for the cost estimation of custom hoses from CAD models. They can come in two formats, which are easy to generate: a STL file or the image of a CAD drawing showing several orthogonal projections. The challenges in either cases are, first, to obtain from them a high level 3D description of the shape, and second, to learn a regression function for the prediction of the manufacturing time, based on geometric features of the reconstructed shape. The chosen description is the 3D line along the medial axis of the tube and the diameter of the circular sections along it. In order to extract it from STL files, we have adapted RANSAC, a robust parametric fitting algorithm. As for CAD drawing images, we propose a new technique for 3D reconstruction from data entered on any number of orthogonal projections. The regression function is a Gaussian process, which does not constrain the function to adopt any specific form and is governed by just two parameters. We assess the accuracy of the manufacturing time estimation by k-fold cross validation on 171 STL file models for which the time is provided by an expert. The results show the feasibility of the method, whereby the relative error for 80% of the testing samples is below 15%. | ||||
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| Publisher | Elsevier | 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 | |||
| Notes | ADAS; 600.057; 600.054; 605.203 | Approved | no | ||
| Call Number | Admin @ si @ SLL2013; ADAS @ adas @ | Serial | 2161 | ||
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| Author | Francisco Javier Orozco; Ognjen Rudovic; Jordi Gonzalez; Maja Pantic | ||||
| Title | Hierarchical On-line Appearance-Based Tracking for 3D Head Pose, Eyebrows, Lips, Eyelids and Irises | Type | Journal Article | ||
| Year | 2013 | Publication | Image and Vision Computing | Abbreviated Journal | IMAVIS |
| Volume | 31 | Issue | 4 | Pages | 322-340 |
| Keywords |
On-line appearance models; Levenberg–Marquardt algorithm; Line-search optimization; 3D face tracking; Facial action tracking; Eyelid tracking; Iris tracking | ||||
| Abstract | In this paper, we propose an On-line Appearance-Based Tracker (OABT) for simultaneous tracking of 3D head pose, lips, eyebrows, eyelids and irises in monocular video sequences. In contrast to previously proposed tracking approaches, which deal with face and gaze tracking separately, our OABT can also be used for eyelid and iris tracking, as well as 3D head pose, lips and eyebrows facial actions tracking. Furthermore, our approach applies an on-line learning of changes in the appearance of the tracked target. Hence, the prior training of appearance models, which usually requires a large amount of labeled facial images, is avoided. Moreover, the proposed method is built upon a hierarchical combination of three OABTs, which are optimized using a Levenberg–Marquardt Algorithm (LMA) enhanced with line-search procedures. This, in turn, makes the proposed method robust to changes in lighting conditions, occlusions and translucent textures, as evidenced by our experiments. Finally, the proposed method achieves head and facial actions tracking in real-time. | ||||
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| Publisher | Elsevier | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
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| Notes | ISE; 605.203; 302.012; 302.018; 600.049 | Approved | no | ||
| Call Number | ORG2013 | Serial | 2221 | ||
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| Author | Joost Van de Weijer; Fahad Shahbaz Khan | ||||
| Title | Fusing Color and Shape for Bag-of-Words Based Object Recognition | Type | Conference Article | ||
| Year | 2013 | Publication | 4th Computational Color Imaging Workshop | Abbreviated Journal | |
| Volume | 7786 | Issue | Pages | 25-34 | |
| Keywords |
Object Recognition; color features; bag-of-words; image classification | ||||
| Abstract | In this article we provide an analysis of existing methods for the incorporation of color in bag-of-words based image representations. We propose a list of desired properties on which bases fusing methods can be compared. We discuss existing methods and indicate shortcomings of the two well-known fusing methods, namely early and late fusion. Several recent works have addressed these shortcomings by exploiting top-down information in the bag-of-words pipeline: color attention which is motivated from human vision, and Portmanteau vocabularies which are based on information theoretic compression of product vocabularies. We point out several remaining challenges in cue fusion and provide directions for future research. | ||||
| Address | Chiba; Japan; March 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 | 978-3-642-36699-4 | Medium | |
| Area | Expedition | Conference | CCIW | ||
| Notes | CIC; 600.048 | Approved | no | ||
| Call Number | Admin @ si @ WeK2013 | Serial | 2283 | ||
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