|
Records |
Links |
|
Author |
Angel Sappa; David Geronimo; Fadi Dornaika; Antonio Lopez |


|
|
Title  |
On-board camera extrinsic parameter estimation |
Type |
Journal Article |
|
Year |
2006 |
Publication |
Electronics Letters |
Abbreviated Journal |
EL |
|
|
Volume |
42 |
Issue |
13 |
Pages |
745–746 |
|
|
Keywords |
|
|
|
Abstract |
An efficient technique for real-time estimation of camera extrinsic parameters is presented. It is intended to be used on on-board vision systems for driving assistance applications. The proposed technique is based on the use of a commercial stereo vision system that does not need any visual feature extraction. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
IEE |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
ADAS |
Approved |
no |
|
|
Call Number |
ADAS @ adas @ SGD2006a |
Serial |
655 |
|
Permanent link to this record |
|
|
|
|
Author |
Javier Marin; David Vazquez; Antonio Lopez; Jaume Amores; Ludmila I. Kuncheva |


|
|
Title  |
Occlusion handling via random subspace classifiers for human detection |
Type |
Journal Article |
|
Year |
2014 |
Publication |
IEEE Transactions on Systems, Man, and Cybernetics (Part B) |
Abbreviated Journal |
TSMCB |
|
|
Volume |
44 |
Issue |
3 |
Pages |
342-354 |
|
|
Keywords |
Pedestriand Detection; occlusion handling |
|
|
Abstract |
This paper describes a general method to address partial occlusions for human detection in still images. The Random Subspace Method (RSM) is chosen for building a classifier ensemble robust against partial occlusions. The component classifiers are chosen on the basis of their individual and combined performance. The main contribution of this work lies in our approach’s capability to improve the detection rate when partial occlusions are present without compromising the detection performance on non occluded data. In contrast to many recent approaches, we propose a method which does not require manual labelling of body parts, defining any semantic spatial components, or using additional data coming from motion or stereo. Moreover, the method can be easily extended to other object classes. The experiments are performed on three large datasets: the INRIA person dataset, the Daimler Multicue dataset, and a new challenging dataset, called PobleSec, in which a considerable number of targets are partially occluded. The different approaches are evaluated at the classification and detection levels for both partially occluded and non-occluded data. The experimental results show that our detector outperforms state-of-the-art approaches in the presence of partial occlusions, while offering performance and reliability similar to those of the holistic approach on non-occluded data. The datasets used in our experiments have been made publicly available for benchmarking purposes |
|
|
Address |
|
|
|
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 |
2168-2267 |
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
ADAS; 605.203; 600.057; 600.054; 601.042; 601.187; 600.076 |
Approved |
no |
|
|
Call Number |
ADAS @ adas @ MVL2014 |
Serial |
2213 |
|
Permanent link to this record |
|
|
|
|
Author |
Joan Serrat; Felipe Lumbreras; Francisco Blanco; Manuel Valiente; Montserrat Lopez-Mesas |


|
|
Title  |
myStone: A system for automatic kidney stone classification |
Type |
Journal Article |
|
Year |
2017 |
Publication |
Expert Systems with Applications |
Abbreviated Journal |
ESA |
|
|
Volume |
89 |
Issue |
|
Pages |
41-51 |
|
|
Keywords |
Kidney stone; Optical device; Computer vision; Image classification |
|
|
Abstract |
Kidney stone formation is a common disease and the incidence rate is constantly increasing worldwide. It has been shown that the classification of kidney stones can lead to an important reduction of the recurrence rate. The classification of kidney stones by human experts on the basis of certain visual color and texture features is one of the most employed techniques. However, the knowledge of how to analyze kidney stones is not widespread, and the experts learn only after being trained on a large number of samples of the different classes. In this paper we describe a new device specifically designed for capturing images of expelled kidney stones, and a method to learn and apply the experts knowledge with regard to their classification. We show that with off the shelf components, a carefully selected set of features and a state of the art classifier it is possible to automate this difficult task to a good degree. We report results on a collection of 454 kidney stones, achieving an overall accuracy of 63% for a set of eight classes covering almost all of the kidney stones taxonomy. Moreover, for more than 80% of samples the real class is the first or the second most probable class according to the system, being then the patient recommendations for the two top classes similar. This is the first attempt towards the automatic visual classification of kidney stones, and based on the current results we foresee better accuracies with the increase of the dataset size. |
|
|
Address |
|
|
|
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 |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
ADAS; MSIAU; 603.046; 600.122; 600.118 |
Approved |
no |
|
|
Call Number |
Admin @ si @ SLB2017 |
Serial |
3026 |
|
Permanent link to this record |
|
|
|
|
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. |
|
|
Address |
|
|
|
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 |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
ADAS; 600.054; 600.055; 605.203 |
Approved |
no |
|
|
Call Number |
Admin @ si @ BLS2013 |
Serial |
2245 |
|
Permanent link to this record |
|
|
|
|
Author |
Cristhian Aguilera; Fernando Barrera; Felipe Lumbreras; Angel Sappa; Ricardo Toledo |


|
|
Title  |
Multispectral Image Feature Points |
Type |
Journal Article |
|
Year |
2012 |
Publication |
Sensors |
Abbreviated Journal |
SENS |
|
|
Volume |
12 |
Issue |
9 |
Pages |
12661-12672 |
|
|
Keywords |
multispectral image descriptor; color and infrared images; feature point descriptor |
|
|
Abstract |
Far-Infrared and Visible Spectrum images. It allows matching interest points on images of the same scene but acquired in different spectral bands. Initially, points of interest are detected on both images through a SIFT-like based scale space representation. Then, these points are characterized using an Edge Oriented Histogram (EOH) descriptor. Finally, points of interest from multispectral images are matched by finding nearest couples using the information from the descriptor. The provided experimental results and comparisons with similar methods show both the validity of the proposed approach as well as the improvements it offers with respect to the current state-of-the-art. |
|
|
Address |
|
|
|
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 |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
ADAS |
Approved |
no |
|
|
Call Number |
Admin @ si @ ABL2012 |
Serial |
2154 |
|
Permanent link to this record |
|
|
|
|
Author |
Jose Carlos Rubio; Joan Serrat; Antonio Lopez; Daniel Ponsa |


|
|
Title  |
Multiple target tracking for intelligent headlights control |
Type |
Journal Article |
|
Year |
2012 |
Publication |
IEEE Transactions on Intelligent Transportation Systems |
Abbreviated Journal |
TITS |
|
|
Volume |
13 |
Issue |
2 |
Pages |
594-605 |
|
|
Keywords |
Intelligent Headlights |
|
|
Abstract |
Intelligent vehicle lighting systems aim at automatically regulating the headlights' beam to illuminate as much of the road ahead as possible while avoiding dazzling other drivers. A key component of such a system is computer vision software that is able to distinguish blobs due to vehicles' headlights and rear lights from those due to road lamps and reflective elements such as poles and traffic signs. In a previous work, we have devised a set of specialized supervised classifiers to make such decisions based on blob features related to its intensity and shape. Despite the overall good performance, there remain challenging that have yet to be solved: notably, faint and tiny blobs corresponding to quite distant vehicles. In fact, for such distant blobs, classification decisions can be taken after observing them during a few frames. Hence, incorporating tracking could improve the overall lighting system performance by enforcing the temporal consistency of the classifier decision. Accordingly, this paper focuses on the problem of constructing blob tracks, which is actually one of multiple-target tracking (MTT), but under two special conditions: We have to deal with frequent occlusions, as well as blob splits and merges. We approach it in a novel way by formulating the problem as a maximum a posteriori inference on a Markov random field. The qualitative (in video form) and quantitative evaluation of our new MTT method shows good tracking results. In addition, we will also see that the classification performance of the problematic blobs improves due to the proposed MTT algorithm. |
|
|
Address |
|
|
|
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 |
1524-9050 |
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
ADAS |
Approved |
no |
|
|
Call Number |
Admin @ si @ RLP2012; ADAS @ adas @ rsl2012g |
Serial |
1877 |
|
Permanent link to this record |
|
|
|
|
Author |
Jaume Amores |


|
|
Title  |
Multiple Instance Classification: review, taxonomy and comparative study |
Type |
Journal Article |
|
Year |
2013 |
Publication |
Artificial Intelligence |
Abbreviated Journal |
AI |
|
|
Volume |
201 |
Issue |
|
Pages |
81-105 |
|
|
Keywords |
Multi-instance learning; Codebook; Bag-of-Words |
|
|
Abstract |
Multiple Instance Learning (MIL) has become an important topic in the pattern recognition community, and many solutions to this problemhave been proposed until now. Despite this fact, there is a lack of comparative studies that shed light into the characteristics and behavior of the different methods. In this work we provide such an analysis focused on the classification task (i.e.,leaving out other learning tasks such as regression). In order to perform our study, we implemented
fourteen methods grouped into three different families. We analyze the performance of the approaches across a variety of well-known databases, and we also study their behavior in synthetic scenarios in order to highlight their characteristics. As a result of this analysis, we conclude that methods that extract global bag-level information show a clearly superior performance in general. In this sense, the analysis permits us to understand why some types of methods are more successful than others, and it permits us to establish guidelines in the design of new MIL
methods. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Elsevier Science Publishers Ltd. Essex, UK |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
0004-3702 |
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
ADAS; 601.042; 600.057 |
Approved |
no |
|
|
Call Number |
Admin @ si @ Amo2013 |
Serial |
2273 |
|
Permanent link to this record |
|
|
|
|
Author |
Fernando Barrera; Felipe Lumbreras; Angel Sappa |


|
|
Title  |
Multimodal Stereo Vision System: 3D Data Extraction and Algorithm Evaluation |
Type |
Journal Article |
|
Year |
2012 |
Publication |
IEEE Journal of Selected Topics in Signal Processing |
Abbreviated Journal |
J-STSP |
|
|
Volume |
6 |
Issue |
5 |
Pages |
437-446 |
|
|
Keywords |
|
|
|
Abstract |
This paper proposes an imaging system for computing sparse depth maps from multispectral images. A special stereo head consisting of an infrared and a color camera defines the proposed multimodal acquisition system. The cameras are rigidly attached so that their image planes are parallel. Details about the calibration and image rectification procedure are provided. Sparse disparity maps are obtained by the combined use of mutual information enriched with gradient information. The proposed approach is evaluated using a Receiver Operating Characteristics curve. Furthermore, a multispectral dataset, color and infrared images, together with their corresponding ground truth disparity maps, is generated and used as a test bed. Experimental results in real outdoor scenarios are provided showing its viability and that the proposed approach is not restricted to a specific domain. |
|
|
Address |
|
|
|
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 |
1932-4553 |
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
ADAS |
Approved |
no |
|
|
Call Number |
Admin @ si @ BLS2012b |
Serial |
2155 |
|
Permanent link to this record |
|
|
|
|
Author |
Miguel Oliveira; Victor Santos; Angel Sappa |

|
|
Title  |
Multimodal Inverse Perspective Mapping |
Type |
Journal Article |
|
Year |
2015 |
Publication |
Information Fusion |
Abbreviated Journal |
IF |
|
|
Volume |
24 |
Issue |
|
Pages |
108–121 |
|
|
Keywords |
Inverse perspective mapping; Multimodal sensor fusion; Intelligent vehicles |
|
|
Abstract |
Over the past years, inverse perspective mapping has been successfully applied to several problems in the field of Intelligent Transportation Systems. In brief, the method consists of mapping images to a new coordinate system where perspective effects are removed. The removal of perspective associated effects facilitates road and obstacle detection and also assists in free space estimation. There is, however, a significant limitation in the inverse perspective mapping: the presence of obstacles on the road disrupts the effectiveness of the mapping. The current paper proposes a robust solution based on the use of multimodal sensor fusion. Data from a laser range finder is fused with images from the cameras, so that the mapping is not computed in the regions where obstacles are present. As shown in the results, this considerably improves the effectiveness of the algorithm and reduces computation time when compared with the classical inverse perspective mapping. Furthermore, the proposed approach is also able to cope with several cameras with different lenses or image resolutions, as well as dynamic viewpoints. |
|
|
Address |
|
|
|
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 |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
ADAS; 600.055; 600.076 |
Approved |
no |
|
|
Call Number |
Admin @ si @ OSS2015c |
Serial |
2532 |
|
Permanent link to this record |
|
|
|
|
Author |
Henry Velesaca; Gisel Bastidas-Guacho; Mohammad Rouhani; Angel Sappa |

|
|
Title  |
Multimodal image registration techniques: a comprehensive survey |
Type |
Journal Article |
|
Year |
2024 |
Publication |
Multimedia Tools and Applications |
Abbreviated Journal |
MTAP |
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
|
|
|
Abstract |
This manuscript presents a review of state-of-the-art techniques proposed in the literature for multimodal image registration, addressing instances where images from different modalities need to be precisely aligned in the same reference system. This scenario arises when the images to be registered come from different modalities, among the visible and thermal spectral bands, 3D-RGB, or flash-no flash, or NIR-visible. The review spans different techniques from classical approaches to more modern ones based on deep learning, aiming to highlight the particularities required at each step in the registration pipeline when dealing with multimodal images. It is noteworthy that medical images are excluded from this review due to their specific characteristics, including the use of both active and passive sensors or the non-rigid nature of the body contained in the image. |
|
|
Address |
|
|
|
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 |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
MSIAU;ADAS |
Approved |
no |
|
|
Call Number |
Admin @ si @ VBR2024 |
Serial |
3997 |
|
Permanent link to this record |