| Records |
| Author |
Bogdan Raducanu; Fadi Dornaika |
| Title |
Embedding new observations via sparse-coding for non-linear manifold learning |
Type |
Journal Article |
| Year |
2014 |
Publication |
Pattern Recognition |
Abbreviated Journal |
PR |
| Volume |
47 |
Issue  |
1 |
Pages |
480-492 |
| Keywords |
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| Abstract |
Non-linear dimensionality reduction techniques are affected by two critical aspects: (i) the design of the adjacency graphs, and (ii) the embedding of new test data-the out-of-sample problem. For the first aspect, the proposed solutions, in general, were heuristically driven. For the second aspect, the difficulty resides in finding an accurate mapping that transfers unseen data samples into an existing manifold. Past works addressing these two aspects were heavily parametric in the sense that the optimal performance is only achieved for a suitable parameter choice that should be known in advance. In this paper, we demonstrate that the sparse representation theory not only serves for automatic graph construction as shown in recent works, but also represents an accurate alternative for out-of-sample embedding. Considering for a case study the Laplacian Eigenmaps, we applied our method to the face recognition problem. To evaluate the effectiveness of the proposed out-of-sample embedding, experiments are conducted using the K-nearest neighbor (KNN) and Kernel Support Vector Machines (KSVM) classifiers on six public face datasets. The experimental results show that the proposed model is able to achieve high categorization effectiveness as well as high consistency with non-linear embeddings/manifolds obtained in batch modes. |
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Conference |
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| Notes |
LAMP; |
Approved |
no |
| Call Number |
Admin @ si @ RaD2013b |
Serial |
2316 |
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| 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 |
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| 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 |
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Thesis |
Ph.D. thesis |
| Publisher |
Ediciones Graficas Rey |
Place of Publication |
Barcelona |
Editor |
Antonio Lopez;Daniel Ponsa |
| Language |
English |
Summary Language |
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Original Title |
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Series Title |
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Series Issue |
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Edition |
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ISBN |
978-84-940530-1-6 |
Medium |
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Expedition |
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Conference |
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| Notes |
adas |
Approved |
yes |
| Call Number |
ADAS @ adas @ Vaz2013 |
Serial |
2276 |
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| Author |
Jose Manuel Alvarez; Theo Gevers; Ferran Diego; Antonio Lopez |
| Title |
Road Geometry Classification by Adaptative Shape Models |
Type |
Journal Article |
| Year |
2013 |
Publication |
IEEE Transactions on Intelligent Transportation Systems |
Abbreviated Journal |
TITS |
| Volume |
14 |
Issue |
1 |
Pages |
459-468 |
| Keywords |
road detection |
| Abstract |
Vision-based road detection is important for different applications in transportation, such as autonomous driving, vehicle collision warning, and pedestrian crossing detection. Common approaches to road detection are based on low-level road appearance (e.g., color or texture) and neglect of the scene geometry and context. Hence, using only low-level features makes these algorithms highly depend on structured roads, road homogeneity, and lighting conditions. Therefore, the aim of this paper is to classify road geometries for road detection through the analysis of scene composition and temporal coherence. Road geometry classification is proposed by building corresponding models from training images containing prototypical road geometries. We propose adaptive shape models where spatial pyramids are steered by the inherent spatial structure of road images. To reduce the influence of lighting variations, invariant features are used. Large-scale experiments show that the proposed road geometry classifier yields a high recognition rate of 73.57% ± 13.1, clearly outperforming other state-of-the-art methods. Including road shape information improves road detection results over existing appearance-based methods. Finally, it is shown that invariant features and temporal information provide robustness against disturbing imaging conditions. |
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Series Title |
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Abbreviated Series Title |
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Series Issue |
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Edition |
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| ISSN |
1524-9050 |
ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
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| Notes |
ADAS;ISE |
Approved |
no |
| Call Number |
Admin @ si @ AGD2013;; ADAS @ adas @ |
Serial |
2269 |
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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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Edition |
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Medium |
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Expedition |
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Conference |
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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 |
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 |
| Keywords |
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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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Edition |
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| ISSN |
1524-9050 |
ISBN |
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Medium |
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Expedition |
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Conference |
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| Notes |
ADAS; 600.076 |
Approved |
no |
| Call Number |
Admin @ si @ OnS2014a |
Serial |
2386 |
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| Author |
Cesar Isaza; Joaquin Salas; Bogdan Raducanu |
| Title |
Rendering ground truth data sets to detect shadows cast by static objects in outdoors |
Type |
Journal Article |
| Year |
2014 |
Publication |
Multimedia Tools and Applications |
Abbreviated Journal |
MTAP |
| Volume |
70 |
Issue |
1 |
Pages |
557-571 |
| Keywords |
Synthetic ground truth data set; Sun position; Shadow detection; Static objects shadow detection |
| Abstract |
In our work, we are particularly interested in studying the shadows cast by static objects in outdoor environments, during daytime. To assess the accuracy of a shadow detection algorithm, we need ground truth information. The collection of such information is a very tedious task because it is a process that requires manual annotation. To overcome this severe limitation, we propose in this paper a methodology to automatically render ground truth using a virtual environment. To increase the degree of realism and usefulness of the simulated environment, we incorporate in the scenario the precise longitude, latitude and elevation of the actual location of the object, as well as the sun’s position for a given time and day. To evaluate our method, we consider a qualitative and a quantitative comparison. In the quantitative one, we analyze the shadow cast by a real object in a particular geographical location and its corresponding rendered model. To evaluate qualitatively the methodology, we use some ground truth images obtained both manually and automatically. |
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Thesis |
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| Publisher |
Springer US |
Place of Publication |
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Editor |
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Summary Language |
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Original Title |
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Series Title |
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Abbreviated Series Title |
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Series Issue |
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Edition |
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| ISSN |
1380-7501 |
ISBN |
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Medium |
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Expedition |
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Conference |
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| Notes |
LAMP; |
Approved |
no |
| Call Number |
Admin @ si @ ISR2014 |
Serial |
2229 |
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| Author |
Laura Igual; Agata Lapedriza; Ricard Borras |
| Title |
Robust Gait-Based Gender Classification using Depth Cameras |
Type |
Journal Article |
| Year |
2013 |
Publication |
EURASIP Journal on Advances in Signal Processing |
Abbreviated Journal |
EURASIPJ |
| Volume |
37 |
Issue |
1 |
Pages |
72-80 |
| Keywords |
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| Abstract |
This article presents a new approach for gait-based gender recognition using depth cameras, that can run in real time. The main contribution of this study is a new fast feature extraction strategy that uses the 3D point cloud obtained from the frames in a gait cycle. For each frame, these points are aligned according to their centroid and grouped. After that, they are projected into their PCA plane, obtaining a representation of the cycle particularly robust against view changes. Then, final discriminative features are computed by first making a histogram of the projected points and then using linear discriminant analysis. To test the method we have used the DGait database, which is currently the only publicly available database for gait analysis that includes depth information. We have performed experiments on manually labeled cycles and over whole video sequences, and the results show that our method improves the accuracy significantly, compared with state-of-the-art systems which do not use depth information. Furthermore, our approach is insensitive to illumination changes, given that it discards the RGB information. That makes the method especially suitable for real applications, as illustrated in the last part of the experiments section. |
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Edition |
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| Notes |
MILAB; OR;MV |
Approved |
no |
| Call Number |
Admin @ si @ ILB2013 |
Serial |
2144 |
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| Author |
Michal Drozdzal; Santiago Segui; Carolina Malagelada; Fernando Azpiroz; Petia Radeva |
| Title |
Adaptable image cuts for motility inspection using WCE |
Type |
Journal Article |
| Year |
2013 |
Publication |
Computerized Medical Imaging and Graphics |
Abbreviated Journal |
CMIG |
| Volume |
37 |
Issue |
1 |
Pages |
72-80 |
| Keywords |
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| Abstract |
The Wireless Capsule Endoscopy (WCE) technology allows the visualization of the whole small intestine tract. Since the capsule is freely moving, mainly by the means of peristalsis, the data acquired during the study gives a lot of information about the intestinal motility. However, due to: (1) huge amount of frames, (2) complex intestinal scene appearance and (3) intestinal dynamics that make difficult the visualization of the small intestine physiological phenomena, the analysis of the WCE data requires computer-aided systems to speed up the analysis. In this paper, we propose an efficient algorithm for building a novel representation of the WCE video data, optimal for motility analysis and inspection. The algorithm transforms the 3D video data into 2D longitudinal view by choosing the most informative, from the intestinal motility point of view, part of each frame. This step maximizes the lumen visibility in its longitudinal extension. The task of finding “the best longitudinal view” has been defined as a cost function optimization problem which global minimum is obtained by using Dynamic Programming. Validation on both synthetic data and WCE data shows that the adaptive longitudinal view is a good alternative to the traditional motility analysis done by video analysis. The proposed novel data representation a new, holistic insight into the small intestine motility, allowing to easily define and analyze motility events that are difficult to spot by analyzing WCE video. Moreover, the visual inspection of small intestine motility is 4 times faster then by means of video skimming of the WCE. |
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| Notes |
MILAB; OR; 600.046; 605.203 |
Approved |
no |
| Call Number |
Admin @ si @ DSM2012 |
Serial |
2151 |
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| Author |
Fadi Dornaika; Abdelmalik Moujahid; Bogdan Raducanu |
| Title |
Facial expression recognition using tracked facial actions: Classifier performance analysis |
Type |
Journal Article |
| Year |
2013 |
Publication |
Engineering Applications of Artificial Intelligence |
Abbreviated Journal |
EAAI |
| Volume |
26 |
Issue |
1 |
Pages |
467-477 |
| Keywords |
Visual face tracking; 3D deformable models; Facial actions; Dynamic facial expression recognition; Human–computer interaction |
| Abstract |
In this paper, we address the analysis and recognition of facial expressions in continuous videos. More precisely, we study classifiers performance that exploit head pose independent temporal facial action parameters. These are provided by an appearance-based 3D face tracker that simultaneously provides the 3D head pose and facial actions. The use of such tracker makes the recognition pose- and texture-independent. Two different schemes are studied. The first scheme adopts a dynamic time warping technique for recognizing expressions where training data are given by temporal signatures associated with different universal facial expressions. The second scheme models temporal signatures associated with facial actions with fixed length feature vectors (observations), and uses some machine learning algorithms in order to recognize the displayed expression. Experiments quantified the performance of different schemes. These were carried out on CMU video sequences and home-made video sequences. The results show that the use of dimension reduction techniques on the extracted time series can improve the classification performance. Moreover, these experiments show that the best recognition rate can be above 90%. |
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Elsevier |
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OR; 600.046;MV |
Approved |
no |
| Call Number |
Admin @ si @ DMR2013 |
Serial |
2185 |
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| Author |
Rozenn Dhayot; Fernando Vilariño; Gerard Lacey |
| Title |
Improving the Quality of Color Colonoscopy Videos |
Type |
Journal Article |
| Year |
2008 |
Publication |
EURASIP Journal on Image and Video Processing |
Abbreviated Journal |
EURASIP JIVP |
| Volume |
139429 |
Issue |
1 |
Pages |
1-9 |
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800 |
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MV;SIAI |
Approved |
no |
| Call Number |
fernando @ fernando @ |
Serial |
2422 |
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| Author |
Shida Beigpour; Christian Riess; Joost Van de Weijer; Elli Angelopoulou |
| Title |
Multi-Illuminant Estimation with Conditional Random Fields |
Type |
Journal Article |
| Year |
2014 |
Publication |
IEEE Transactions on Image Processing |
Abbreviated Journal |
TIP |
| Volume |
23 |
Issue |
1 |
Pages |
83-95 |
| Keywords |
color constancy; CRF; multi-illuminant |
| Abstract |
Most existing color constancy algorithms assume uniform illumination. However, in real-world scenes, this is not often the case. Thus, we propose a novel framework for estimating the colors of multiple illuminants and their spatial distribution in the scene. We formulate this problem as an energy minimization task within a conditional random field over a set of local illuminant estimates. In order to quantitatively evaluate the proposed method, we created a novel data set of two-dominant-illuminant images comprised of laboratory, indoor, and outdoor scenes. Unlike prior work, our database includes accurate pixel-wise ground truth illuminant information. The performance of our method is evaluated on multiple data sets. Experimental results show that our framework clearly outperforms single illuminant estimators as well as a recently proposed multi-illuminant estimation approach. |
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1057-7149 |
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CIC; LAMP; 600.074; 600.079 |
Approved |
no |
| Call Number |
Admin @ si @ BRW2014 |
Serial |
2451 |
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| Author |
Victor Ponce; Sergio Escalera; Marc Perez; Oriol Janes; Xavier Baro |
| Title |
Non-Verbal Communication Analysis in Victim-Offender Mediations |
Type |
Journal Article |
| Year |
2015 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
| Volume |
67 |
Issue |
1 |
Pages |
19-27 |
| Keywords |
Victim–Offender Mediation; Multi-modal human behavior analysis; Face and gesture recognition; Social signal processing; Computer vision; Machine learning |
| Abstract |
We present a non-invasive ambient intelligence framework for the semi-automatic analysis of non-verbal communication applied to the restorative justice field. We propose the use of computer vision and social signal processing technologies in real scenarios of Victim–Offender Mediations, applying feature extraction techniques to multi-modal audio-RGB-depth data. We compute a set of behavioral indicators that define communicative cues from the fields of psychology and observational methodology. We test our methodology on data captured in real Victim–Offender Mediation sessions in Catalonia. We define the ground truth based on expert opinions when annotating the observed social responses. Using different state of the art binary classification approaches, our system achieves recognition accuracies of 86% when predicting satisfaction, and 79% when predicting both agreement and receptivity. Applying a regression strategy, we obtain a mean deviation for the predictions between 0.5 and 0.7 in the range [1–5] for the computed social signals. |
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HuPBA;MV |
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no |
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Admin @ si @ PEP2015 |
Serial |
2583 |
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| Author |
Victor Ponce; Mario Gorga; Xavier Baro; Petia Radeva; Sergio Escalera |
| Title |
Análisis de la expresión oral y gestual en proyectos fin de carrera vía un sistema de visión artificial |
Type |
Journal Article |
| Year |
2011 |
Publication |
ReVisión |
Abbreviated Journal |
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| Volume |
4 |
Issue |
1 |
Pages |
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| Abstract |
La comunicación y expresión oral es una competencia de especial relevancia en el EEES. No obstante, en muchas enseñanzas superiores la puesta en práctica de esta competencia ha sido relegada principalmente a la presentación de proyectos fin de carrera. Dentro de un proyecto de innovación docente, se ha desarrollado una herramienta informática para la extracción de información objetiva para el análisis de la expresión oral y gestual de los alumnos. El objetivo es dar un “feedback” a los estudiantes que les permita mejorar la calidad de sus presentaciones. El prototipo inicial que se presenta en este trabajo permite extraer de forma automática información audiovisual y analizarla mediante técnicas de aprendizaje. El sistema ha sido aplicado a 15 proyectos fin de carrera y 15 exposiciones dentro de una asignatura de cuarto curso. Los resultados obtenidos muestran la viabilidad del sistema para sugerir factores que ayuden tanto en el éxito de la comunicación así como en los criterios de evaluación. |
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1989-1199 |
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HuPBA; MILAB;MV |
Approved |
no |
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Admin @ si @ PGB2011d |
Serial |
2514 |
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| Author |
Mohammad Rouhani; Angel Sappa; E. Boyer |
| Title |
Implicit B-Spline Surface Reconstruction |
Type |
Journal Article |
| Year |
2015 |
Publication |
IEEE Transactions on Image Processing |
Abbreviated Journal |
TIP |
| Volume |
24 |
Issue |
1 |
Pages |
22 - 32 |
| Keywords |
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| Abstract |
This paper presents a fast and flexible curve, and surface reconstruction technique based on implicit B-spline. This representation does not require any parameterization and it is locally supported. This fact has been exploited in this paper to propose a reconstruction technique through solving a sparse system of equations. This method is further accelerated to reduce the dimension to the active control lattice. Moreover, the surface smoothness and user interaction are allowed for controlling the surface. Finally, a novel weighting technique has been introduced in order to blend small patches and smooth them in the overlapping regions. The whole framework is very fast and efficient and can handle large cloud of points with very low computational cost. The experimental results show the flexibility and accuracy of the proposed algorithm to describe objects with complex topologies. Comparisons with other fitting methods highlight the superiority of the proposed approach in the presence of noise and missing data. |
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Edition |
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| ISSN |
1057-7149 |
ISBN |
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Conference |
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| Notes |
ADAS; 600.076 |
Approved |
no |
| Call Number |
Admin @ si @ RSB2015 |
Serial |
2541 |
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| Author |
Alvaro Cepero; Albert Clapes; Sergio Escalera |
| Title |
Automatic non-verbal communication skills analysis: a quantitative evaluation |
Type |
Journal Article |
| Year |
2015 |
Publication |
AI Communications |
Abbreviated Journal |
AIC |
| Volume |
28 |
Issue |
1 |
Pages |
87-101 |
| Keywords |
Social signal processing; human behavior analysis; multi-modal data description; multi-modal data fusion; non-verbal communication analysis; e-Learning |
| Abstract |
The oral communication competence is defined on the top of the most relevant skills for one's professional and personal life. Because of the importance of communication in our activities of daily living, it is crucial to study methods to evaluate and provide the necessary feedback that can be used in order to improve these communication capabilities and, therefore, learn how to express ourselves better. In this work, we propose a system capable of evaluating quantitatively the quality of oral presentations in an automatic fashion. The system is based on a multi-modal RGB, depth, and audio data description and a fusion approach in order to recognize behavioral cues and train classifiers able to eventually predict communication quality levels. The performance of the proposed system is tested on a novel dataset containing Bachelor thesis' real defenses, presentations from an 8th semester Bachelor courses, and Master courses' presentations at Universitat de Barcelona. Using as groundtruth the marks assigned by actual instructors, our system achieves high performance categorizing and ranking presentations by their quality, and also making real-valued mark predictions. |
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Edition |
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| ISSN |
0921-7126 |
ISBN |
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Conference |
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| Notes |
HUPBA;MILAB |
Approved |
no |
| Call Number |
Admin @ si @ CCE2015 |
Serial |
2549 |
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