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Author |
Aura Hernandez-Sabate; Debora Gil |
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Title |
The Benefits of IVUS Dynamics for Retrieving Stable Models of Arteries |
Type |
Book Chapter |
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Year |
2012 |
Publication |
Intravascular Ultrasound |
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Pages |
185-206 |
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Publisher |
Intech |
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Editor |
Yasuhiro Honda |
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Language |
English |
Summary Language |
english |
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978-953-307-900-4 |
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Notes |
IAM; ADAS |
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no |
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Call Number |
IAM @ iam @ HeG2012 |
Serial |
1684 |
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Author |
Ferran Diego |
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Title |
Probabilistic Alignment of Video Sequences Recorded by Moving Cameras |
Type |
Book Whole |
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Year |
2011 |
Publication |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Video alignment consists of integrating multiple video sequences recorded independently into a single video sequence. This means to register both in time (synchronize
frames) and space (image registration) so that the two videos sequences can be fused
or compared pixel–wise. In spite of being relatively unknown, many applications today may benefit from the availability of robust and efficient video alignment methods.
For instance, video surveillance requires to integrate video sequences that are recorded
of the same scene at different times in order to detect changes. The problem of aligning videos has been addressed before, but in the relatively simple cases of fixed or rigidly attached cameras and simultaneous acquisition. In addition, most works rely
on restrictive assumptions which reduce its difficulty such as linear time correspondence or the knowledge of the complete trajectories of corresponding scene points on the images; to some extent, these assumptions limit the practical applicability of the solutions developed until now. In this thesis, we focus on the challenging problem of aligning sequences recorded at different times from independent moving cameras following similar but not coincident trajectories. More precisely, this thesis covers four studies that advance the state-of-the-art in video alignment. First, we focus on analyzing and developing a probabilistic framework for video alignment, that is, a principled way to integrate multiple observations and prior information. In this way, two different approaches are presented to exploit the combination of several purely visual features (image–intensities, visual words and dense motion field descriptor), and
global positioning system (GPS) information. Second, we focus on reformulating the
problem into a single alignment framework since previous works on video alignment
adopt a divide–and–conquer strategy, i.e., first solve the synchronization, and then
register corresponding frames. This also generalizes the ’classic’ case of fixed geometric transform and linear time mapping. Third, we focus on exploiting directly the
time domain of the video sequences in order to avoid exhaustive cross–frame search.
This provides relevant information used for learning the temporal mapping between
pairs of video sequences. Finally, we focus on adapting these methods to the on–line
setting for road detection and vehicle geolocation. The qualitative and quantitative
results presented in this thesis on a variety of real–world pairs of video sequences show that the proposed method is: robust to varying imaging conditions, different image
content (e.g., incoming and outgoing vehicles), variations on camera velocity, and
different scenarios (indoor and outdoor) going beyond the state–of–the–art. Moreover, the on–line video alignment has been successfully applied for road detection and
vehicle geolocation achieving promising results. |
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Thesis |
Ph.D. thesis |
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Publisher |
Ediciones Graficas Rey |
Place of Publication |
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Editor |
Joan Serrat |
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ADAS |
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no |
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Call Number |
Admin @ si @ Die2011 |
Serial |
1787 |
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Author |
Javier Marin; David Geronimo; David Vazquez; Antonio Lopez |
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Title |
Pedestrian Detection: Exploring Virtual Worlds |
Type |
Book Chapter |
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Year |
2012 |
Publication |
Handbook of Pattern Recognition: Methods and Application |
Abbreviated Journal |
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Volume |
5 |
Issue |
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Pages |
145-162 |
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Keywords |
Virtual worlds; Pedestrian Detection; Domain Adaptation |
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Abstract |
Handbook of pattern recognition will include contributions from university educators and active research experts. This Handbook is intended to serve as a basic reference on methods and applications of pattern recognition. The primary aim of this handbook is providing the community of pattern recognition with a readable, easy to understand resource that covers introductory, intermediate and advanced topics with equal clarity. Therefore, the Handbook of pattern recognition can serve equally well as reference resource and as classroom textbook. Contributions cover all methods, techniques and applications of pattern recognition. A tentative list of relevant topics might include: 1- Statistical, structural, syntactic pattern recognition. 2- Neural networks, machine learning, data mining. 3- Discrete geometry, algebraic, graph-based techniques for pattern recognition. 4- Face recognition, Signal analysis, image coding and processing, shape and texture analysis. 5- Document processing, text and graphics recognition, digital libraries. 6- Speech recognition, music analysis, multimedia systems. 7- Natural language analysis, information retrieval. 8- Biometrics, biomedical pattern analysis and information systems. 9- Other scientific, engineering, social and economical applications of pattern recognition. 10- Special hardware architectures, software packages for pattern recognition. |
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Publisher |
iConcept Press |
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English |
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ISBN |
978-1-477554-82-1 |
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Notes |
ADAS |
Approved |
no |
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Call Number |
ADAS @ adas @ MGV2012 |
Serial |
1979 |
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Author |
David Geronimo; Antonio Lopez |
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Title |
Vision-based Pedestrian Protection Systems for Intelligent Vehicles |
Type |
Book Whole |
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Year |
2014 |
Publication |
SpringerBriefs in Computer Science |
Abbreviated Journal |
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Pages |
1-114 |
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Keywords |
Computer Vision; Driver Assistance Systems; Intelligent Vehicles; Pedestrian Detection; Vulnerable Road Users |
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Abstract |
Pedestrian Protection Systems (PPSs) are on-board systems aimed at detecting and tracking people in the surroundings of a vehicle in order to avoid potentially dangerous situations. These systems, together with other Advanced Driver Assistance Systems (ADAS) such as lane departure warning or adaptive cruise control, are one of the most promising ways to improve traffic safety. By the use of computer vision, cameras working either in the visible or infra-red spectra have been demonstrated as a reliable sensor to perform this task. Nevertheless, the variability of human’s appearance, not only in terms of clothing and sizes but also as a result of their dynamic shape, makes pedestrians one of the most complex classes even for computer vision. Moreover, the unstructured changing and unpredictable environment in which such on-board systems must work makes detection a difficult task to be carried out with the demanded robustness. In this brief, the state of the art in PPSs is introduced through the review of the most relevant papers of the last decade. A common computational architecture is presented as a framework to organize each method according to its main contribution. More than 300 papers are referenced, most of them addressing pedestrian detection and others corresponding to the descriptors (features), pedestrian models, and learning machines used. In addition, an overview of topics such as real-time aspects, systems benchmarking and future challenges of this research area are presented. |
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Publisher |
Springer Briefs in Computer Vision |
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ISBN |
978-1-4614-7986-4 |
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Notes |
ADAS; 600.076 |
Approved |
no |
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Call Number |
GeL2014 |
Serial |
2325 |
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Permanent link to this record |
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Author |
Angel Sappa; David Geronimo; Fadi Dornaika; Mohammad Rouhani; Antonio Lopez |
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Title |
Moving object detection from mobile platforms using stereo data registration |
Type |
Book Chapter |
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Year |
2012 |
Publication |
Computational Intelligence paradigms in advanced pattern classification |
Abbreviated Journal |
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Volume |
386 |
Issue |
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Pages |
25-37 |
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Keywords |
pedestrian detection |
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Abstract |
This chapter describes a robust approach for detecting moving objects from on-board stereo vision systems. It relies on a feature point quaternion-based registration, which avoids common problems that appear when computationally expensive iterative-based algorithms are used on dynamic environments. The proposed approach consists of three main stages. Initially, feature points are extracted and tracked through consecutive 2D frames. Then, a RANSAC based approach is used for registering two point sets, with known correspondences in the 3D space. The computed 3D rigid displacement is used to map two consecutive 3D point clouds into the same coordinate system by means of the quaternion method. Finally, moving objects correspond to those areas with large 3D registration errors. Experimental results show the viability of the proposed approach to detect moving objects like vehicles or pedestrians in different urban scenarios. |
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Springer Berlin Heidelberg |
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Editor |
Marek R. Ogiela; Lakhmi C. Jain |
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ISSN |
1860-949X |
ISBN |
978-3-642-24048-5 |
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Notes |
ADAS |
Approved |
no |
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Call Number |
Admin @ si @ SGD2012 |
Serial |
2061 |
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Permanent link to this record |
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Author |
Cristhian Aguilera; M.Ramos; Angel Sappa |
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Title |
Simulated Annealing: A Novel Application of Image Processing in the Wood Area |
Type |
Book Chapter |
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Year |
2012 |
Publication |
Simulated Annealing – Advances, Applications and Hybridizations |
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Pages |
91-104 |
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Editor |
Marcos de Sales Guerra Tsuzuki |
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ISBN |
978-953-51-0710-1 |
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Notes |
ADAS |
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no |
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Call Number |
Admin @ si @ ARS2012 |
Serial |
2156 |
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Author |
Jose Manuel Alvarez; Antonio Lopez |
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Title |
Photometric Invariance by Machine Learning |
Type |
Book Chapter |
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Year |
2012 |
Publication |
Color in Computer Vision: Fundamentals and Applications |
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Volume |
7 |
Issue |
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Pages |
113-134 |
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Keywords |
road detection |
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Publisher |
iConcept Press Ltd |
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Editor |
Theo Gevers, Arjan Gijsenij, Joost van de Weijer, Jan-Mark Geusebroek |
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ISBN |
978-0-470-89084-4 |
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Notes |
ADAS |
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no |
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Call Number |
Admin @ si @ AlL2012 |
Serial |
2186 |
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Author |
Angel Sappa; Jordi Vitria |
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Title |
Multimodal Interaction in Image and Video Applications |
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Book Whole |
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Year |
2013 |
Publication |
Multimodal Interaction in Image and Video Applications |
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Volume |
48 |
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Abstract |
Book Series Intelligent Systems Reference Library |
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Springer Berlin Heidelberg |
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ISSN |
1868-4394 |
ISBN |
978-3-642-35931-6 |
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Notes |
ADAS; OR;MV |
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no |
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Call Number |
Admin @ si @ SaV2013 |
Serial |
2199 |
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Author |
Mohammad Rouhani |
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Title |
Shape Representation and Registration using Implicit Functions |
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Book Whole |
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Year |
2012 |
Publication |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Abstract |
Shape representation and registration are two important problems in computer vision and graphics. Representing the given cloud of points through an implicit function provides a higher level information describing the data. This representation can be more compact more robust to noise and outliers, hence it can be exploited in different computer vision application. In the first part of this thesis implicit shape representations, including both implicit B-spline and polynomial, are tackled. First, an approximation of a geometric distance is proposed to measure the closeness of the given cloud of points and the implicit surface. The analysis of the proposed distance shows an accurate estimation with smooth behavior. The distance by itself is used in a RANSAC based quadratic fitting method. Moreover, since the gradient information of the distance with respect to the surface parameters can be analytically computed, it is used in Levenberg-Marquadt algorithm to refine the surface parameters. In a different approach, an algebraic fitting method is used to represent an object through implicit B-splines. The outcome is a smooth flexible surface and can be represented in different levels from coarse to fine. This property has been exploited to solve the registration problem in the second part of the thesis. In the proposed registration technique the model set is replaced with an implicit representation provided in the first part; then, the point-to-point registration is converted to a point-to-model one in a higher level. This registration error can benefit from different distance estimations to speed up the registration process even without need of correspondence search. Finally, the non-rigid registration problem is tackled through a quadratic distance approximation that is based on the curvature information of the model set. This approximation is used in a free form deformation model to update its control lattice. Then it is shown how an accurate distance approximation can benefit non-rigid registration problems. |
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Thesis |
Ph.D. thesis |
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Publisher |
Ediciones Graficas Rey |
Place of Publication |
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Editor |
Angel Sappa |
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Notes |
ADAS |
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no |
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Call Number |
Admin @ si @ Rou2012 |
Serial |
2205 |
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Permanent link to this record |
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Author |
Jose Carlos Rubio |
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Title |
Many-to-Many High Order Matching. Applications to Tracking and Object Segmentation |
Type |
Book Whole |
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Year |
2012 |
Publication |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Abstract |
Feature matching is a fundamental problem in Computer Vision, having multiple applications such as tracking, image classification and retrieval, shape recognition and stereo fusion. In numerous domains, it is useful to represent the local structure of the matching features to increase the matching accuracy or to make the correspondence invariant to certain transformations (affine, homography, etc. . . ). However, encoding this knowledge requires complicating the model by establishing high-order relationships between the model elements, and therefore increasing the complexity of the optimization problem.
The importance of many-to-many matching is sometimes dismissed in the literature. Most methods are restricted to perform one-to-one matching, and are usually validated on synthetic, or non-realistic datasets. In a real challenging environment, with scale, pose and illumination variations of the object of interest, as well as the presence of occlusions, clutter, and noisy observations, many-to-many matching is necessary to achieve satisfactory results. As a consequence, finding the most likely many-to-many correspondence often involves a challenging combinatorial optimization process.
In this work, we design and demonstrate matching algorithms that compute many-to-many correspondences, applied to several challenging problems. Our goal is to make use of high-order representations to improve the expressive power of the matching, at the same time that we make feasible the process of inference or optimization of such models. We effectively use graphical models as our preferred representation because they provide an elegant probabilistic framework to tackle structured prediction problems.
We introduce a matching-based tracking algorithm which performs matching between frames of a video sequence in order to solve the difficult problem of headlight tracking at night-time. We also generalise this algorithm to solve the problem of data association applied to various tracking scenarios. We demonstrate the effectiveness of such approach in real video sequences and we show that our tracking algorithm can be used to improve the accuracy of a headlight classification system.
In the second part of this work, we move from single (point) matching to dense (region) matching and we introduce a new hierarchical image representation. We make use of such model to develop a high-order many-to-many matching between pairs of images. We show that the use of high-order models in comparison to simpler models improves not only the accuracy of the results, but also the convergence speed of the inference algorithm.
Finally, we keep exploiting the idea of region matching to design a fully unsupervised image co-segmentation algorithm that is able to perform competitively with state-of-the-art supervised methods. Our method also overcomes the typical drawbacks of some of the past works, such as avoiding the necessity of variate appearances on the image backgrounds. The region matching in this case is applied to effectively exploit inter-image information. We also extend this work to perform co-segmentation of videos, being the first time that such problem is addressed, as a way to perform video object segmentation |
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Thesis |
Ph.D. thesis |
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Publisher |
Ediciones Graficas Rey |
Place of Publication |
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Editor |
Joan Serrat |
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Notes |
ADAS |
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no |
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Call Number |
Admin @ si @ Rub2012 |
Serial |
2206 |
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Permanent link to this record |