| Records |
| Author |
Mohammad Rouhani; Angel Sappa |
| Title |
Correspondence Free Registration through a Point-to-Model Distance Minimization |
Type |
Conference Article |
| Year |
2011 |
Publication |
13th IEEE International Conference on Computer Vision |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
2150-2157 |
| Keywords |
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Abstract  |
This paper presents a novel formulation, which derives in a smooth minimization problem, to tackle the rigid registration between a given point set and a model set. Unlike most of the existing works, which are based on minimizing a point-wise correspondence term, we propose to describe the model set by means of an implicit representation. It allows a new definition of the registration error, which works beyond the point level representation. Moreover, it could be used in a gradient-based optimization framework. The proposed approach consists of two stages. Firstly, a novel formulation is proposed that relates the registration parameters with the distance between the model and data set. Secondly, the registration parameters are obtained by means of the Levengberg-Marquardt algorithm. Experimental results and comparisons with state of the art show the validity of the proposed framework. |
| Address |
Barcelona |
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Thesis |
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Place of Publication |
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Editor |
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| Language |
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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 Volume |
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Series Issue |
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Edition |
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| ISSN |
1550-5499 |
ISBN |
978-1-4577-1101-5 |
Medium |
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| Area |
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Expedition |
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Conference |
ICCV |
| Notes |
ADAS |
Approved |
no |
| Call Number |
Admin @ si @ RoS2011b; ADAS @ adas @ |
Serial |
1832 |
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| Author |
Patricia Suarez; Dario Carpio; Angel Sappa |
| Title |
A Deep Learning Based Approach for Synthesizing Realistic Depth Maps |
Type |
Conference Article |
| Year |
2023 |
Publication |
22nd International Conference on Image Analysis and Processing |
Abbreviated Journal |
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| Volume |
14234 |
Issue |
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Pages |
369–380 |
| Keywords |
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| Abstract |
This paper presents a novel cycle generative adversarial network (CycleGAN) architecture for synthesizing high-quality depth maps from a given monocular image. The proposed architecture uses multiple loss functions, including cycle consistency, contrastive, identity, and least square losses, to enable the generation of realistic and high-fidelity depth maps. The proposed approach addresses this challenge by synthesizing depth maps from RGB images without requiring paired training data. Comparisons with several state-of-the-art approaches are provided showing the proposed approach overcome other approaches both in terms of quantitative metrics and visual quality. |
| Address |
Udine; Italia; Setember 2023 |
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Original Title |
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Abbreviated Series Title |
LNCS |
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Series Issue |
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Edition |
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ISBN |
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Medium |
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Expedition |
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Conference |
ICIAP |
| Notes |
MSIAU |
Approved |
no |
| Call Number |
Admin @ si @ SCS2023a |
Serial |
3968 |
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| Author |
Cristhian A. Aguilera-Carrasco; Angel Sappa; Cristhian Aguilera; Ricardo Toledo |
| Title |
Cross-Spectral Local Descriptors via Quadruplet Network |
Type |
Journal Article |
| Year |
2017 |
Publication |
Sensors |
Abbreviated Journal |
SENS |
| Volume |
17 |
Issue |
4 |
Pages |
873 |
| Keywords |
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| Abstract |
This paper presents a novel CNN-based architecture, referred to as Q-Net, to learn local feature descriptors that are useful for matching image patches from two different spectral bands. Given correctly matched and non-matching cross-spectral image pairs, a quadruplet network is trained to map input image patches to a common Euclidean space, regardless of the input spectral band. Our approach is inspired by the recent success of triplet networks in the visible spectrum, but adapted for cross-spectral scenarios, where, for each matching pair, there are always two possible non-matching patches: one for each spectrum. Experimental evaluations on a public cross-spectral VIS-NIR dataset shows that the proposed approach improves the state-of-the-art. Moreover, the proposed technique can also be used in mono-spectral settings, obtaining a similar performance to triplet network descriptors, but requiring less training data. |
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Place of Publication |
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Summary Language |
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Original Title |
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ISBN |
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Medium |
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Expedition |
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Conference |
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| Notes |
ADAS; 600.086; 600.118 |
Approved |
no |
| Call Number |
Admin @ si @ ASA2017 |
Serial |
2914 |
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| |
| Author |
Patricia Suarez; Dario Carpio; Angel Sappa |
| Title |
Non-homogeneous Haze Removal Through a Multiple Attention Module Architecture |
Type |
Conference Article |
| Year |
2021 |
Publication |
16th International Symposium on Visual Computing |
Abbreviated Journal |
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| Volume |
13018 |
Issue |
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Pages |
178–190 |
| Keywords |
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| Abstract |
This paper presents a novel attention based architecture to remove non-homogeneous haze. The proposed model is focused on obtaining the most representative characteristics of the image, at each learning cycle, by means of adaptive attention modules coupled with a residual learning convolutional network. The latter is based on the Res2Net model. The proposed architecture is trained with just a few set of images. Its performance is evaluated on a public benchmark—images from the non-homogeneous haze NTIRE 2021 challenge—and compared with state of the art approaches reaching the best result. |
| Address |
Virtual; October 2021 |
| Corporate Author |
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Place of Publication |
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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 |
LNCS |
| Series Volume |
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Series Issue |
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Edition |
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ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
ISVC |
| Notes |
MSIAU |
Approved |
no |
| Call Number |
Admin @ si @ SCS2021 |
Serial |
3668 |
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| Author |
Patricia Suarez; Dario Carpio; Angel Sappa; Henry Velesaca |
| Title |
Transformer based Image Dehazing |
Type |
Conference Article |
| Year |
2022 |
Publication |
16th IEEE International Conference on Signal Image Technology & Internet Based System |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
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| Keywords |
atmospheric light; brightness component; computational cost; dehazing quality; haze-free image |
| Abstract |
This paper presents a novel approach to remove non homogeneous haze from real images. The proposed method consists mainly of image feature extraction, haze removal, and image reconstruction. To accomplish this challenging task, we propose an architecture based on transformers, which have been recently introduced and have shown great potential in different computer vision tasks. Our model is based on the SwinIR an image restoration architecture based on a transformer, but by modifying the deep feature extraction module, the depth level of the model, and by applying a combined loss function that improves styling and adapts the model for the non-homogeneous haze removal present in images. The obtained results prove to be superior to those obtained by state-of-the-art models. |
| Address |
Dijon; France; October 2022 |
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Original Title |
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Edition |
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ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
SITIS |
| Notes |
MSIAU; no proj |
Approved |
no |
| Call Number |
Admin @ si @ SCS2022 |
Serial |
3803 |
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| |
| Author |
Patricia Suarez; Angel Sappa |
| Title |
A Generative Model for Guided Thermal Image Super-Resolution |
Type |
Conference Article |
| Year |
2024 |
Publication |
19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
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| Keywords |
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| Abstract |
This paper presents a novel approach for thermal super-resolution based on a fusion prior, low-resolution thermal image and H brightness channel of the corresponding visible spectrum image. The method combines bicubic interpolation of the ×8 scale target image with the brightness component. To enhance the guidance process, the original RGB image is converted to HSV, and the brightness channel is extracted. Bicubic interpolation is then applied to the low-resolution thermal image, resulting in a Bicubic-Brightness channel blend. This luminance-bicubic fusion is used as an input image to help the training process. With this fused image, the cyclic adversarial generative network obtains high-resolution thermal image results. Experimental evaluations show that the proposed approach significantly improves spatial resolution and pixel intensity levels compared to other state-of-the-art techniques, making it a promising method to obtain high-resolution thermal. |
| Address |
Roma; Italia; February 2024 |
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Place of Publication |
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Summary Language |
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Original Title |
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Series Title |
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Edition |
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ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
VISAPP |
| Notes |
MSIAU |
Approved |
no |
| Call Number |
Admin @ si @ SuS2024 |
Serial |
4002 |
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| Author |
Angel Sappa; Mohammad Rouhani |
| Title |
Efficient Distance Estimation for Fitting Implicit Quadric Surfaces |
Type |
Conference Article |
| Year |
2009 |
Publication |
16th IEEE International Conference on Image Processing |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
3521–3524 |
| Keywords |
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| Abstract |
This paper presents a novel approach for estimating the shortest Euclidean distance from a given point to the corresponding implicit quadric fitting surface. It first estimates the orthogonal orientation to the surface from the given point; then the shortest distance is directly estimated by intersecting the implicit surface with a line passing through the given point according to the estimated orthogonal orientation. The proposed orthogonal distance estimation is easily obtained without increasing computational complexity; hence it can be used in error minimization surface fitting frameworks. Comparisons of the proposed metric with previous approaches are provided to show both improvements in CPU time as well as in the accuracy of the obtained results. Surfaces fitted by using the proposed geometric distance estimation and state of the art metrics are presented to show the viability of the proposed approach. |
| Address |
Cairo, Egypt |
| Corporate Author |
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Thesis |
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| Publisher |
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Place of Publication |
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Editor |
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| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
1522-4880 |
ISBN |
978-1-4244-5653-6 |
Medium |
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| Area |
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Expedition |
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Conference |
ICIP |
| Notes |
ADAS |
Approved |
no |
| Call Number |
ADAS @ adas @ SaR2009 |
Serial |
1232 |
| Permanent link to this record |
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| |
| Author |
Mohammad Rouhani; Angel Sappa |
| Title |
A Novel Approach to Geometric Fitting of Implicit Quadrics |
Type |
Conference Article |
| Year |
2009 |
Publication |
8th International Conference on Advanced Concepts for Intelligent Vision Systems |
Abbreviated Journal |
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| Volume |
5807 |
Issue |
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Pages |
121–132 |
| Keywords |
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| Abstract |
This paper presents a novel approach for estimating the geometric distance from a given point to the corresponding implicit quadric curve/surface. The proposed estimation is based on the height of a tetrahedron, which is used as a coarse but reliable estimation of the real distance. The estimated distance is then used for finding the best set of quadric parameters, by means of the Levenberg-Marquardt algorithm, which is a common framework in other geometric fitting approaches. Comparisons of the proposed approach with previous ones are provided to show both improvements in CPU time as well as in the accuracy of the obtained results. |
| Address |
Bordeaux, France |
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Thesis |
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| Publisher |
Springer Berlin Heidelberg |
Place of Publication |
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Editor |
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| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
LNCS |
| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
0302-9743 |
ISBN |
978-3-642-04696-4 |
Medium |
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| Area |
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Expedition |
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Conference |
ACIVS |
| Notes |
ADAS |
Approved |
no |
| Call Number |
ADAS @ adas @ RoS2009 |
Serial |
1194 |
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| Author |
Armin Mehri; Angel Sappa |
| Title |
Colorizing Near Infrared Images through a Cyclic Adversarial Approach of Unpaired Samples |
Type |
Conference Article |
| Year |
2019 |
Publication |
IEEE International Conference on Computer Vision and Pattern Recognition-Workshops |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
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| Abstract |
This paper presents a novel approach for colorizing near infrared (NIR) images. The approach is based on image-to-image translation using a Cycle-Consistent adversarial network for learning the color channels on unpaired dataset. This architecture is able to handle unpaired datasets. The approach uses as generators tailored networks that require less computation times, converge faster and generate high quality samples. The obtained results have been quantitatively—using standard evaluation metrics—and qualitatively evaluated showing considerable improvements with respect to the state of the art |
| Address |
Long beach; California; USA; June 2019 |
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Conference |
CVPRW |
| Notes |
MSIAU; 600.130; 601.349; 600.122 |
Approved |
no |
| Call Number |
Admin @ si @ MeS2019 |
Serial |
3271 |
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| Author |
Albert Berenguel; Oriol Ramos Terrades; Josep Llados; Cristina Cañero |
| Title |
e-Counterfeit: a mobile-server platform for document counterfeit detection |
Type |
Conference Article |
| Year |
2017 |
Publication |
14th IAPR International Conference on Document Analysis and Recognition |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
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| Abstract |
This paper presents a novel application to detect counterfeit identity documents forged by a scan-printing operation. Texture analysis approaches are proposed to extract validation features from security background that is usually printed in documents as IDs or banknotes. The main contribution of this work is the end-to-end mobile-server architecture, which provides a service for non-expert users and therefore can be used in several scenarios. The system also provides a crowdsourcing mode so labeled images can be gathered, generating databases for incremental training of the algorithms. |
| Address |
Kyoto; Japan; November 2017 |
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Conference |
ICDAR |
| Notes |
DAG; 600.061; 600.097; 600.121 |
Approved |
no |
| Call Number |
Admin @ si @ BRL2018 |
Serial |
3084 |
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| Author |
Ivan Huerta; Ariel Amato; Xavier Roca; Jordi Gonzalez |
| Title |
Exploiting Multiple Cues in Motion Segmentation Based on Background Subtraction |
Type |
Journal Article |
| Year |
2013 |
Publication |
Neurocomputing |
Abbreviated Journal |
NEUCOM |
| Volume |
100 |
Issue |
|
Pages |
183–196 |
| Keywords |
Motion segmentation; Shadow suppression; Colour segmentation; Edge segmentation; Ghost detection; Background subtraction |
| Abstract |
This paper presents a novel algorithm for mobile-object segmentation from static background scenes, which is both robust and accurate under most of the common problems found in motionsegmentation. In our first contribution, a case analysis of motionsegmentation errors is presented taking into account the inaccuracies associated with different cues, namely colour, edge and intensity. Our second contribution is an hybrid architecture which copes with the main issues observed in the case analysis by fusing the knowledge from the aforementioned three cues and a temporal difference algorithm. On one hand, we enhance the colour and edge models to solve not only global and local illumination changes (i.e. shadows and highlights) but also the camouflage in intensity. In addition, local information is also exploited to solve the camouflage in chroma. On the other hand, the intensity cue is applied when colour and edge cues are not available because their values are beyond the dynamic range. Additionally, temporal difference scheme is included to segment motion where those three cues cannot be reliably computed, for example in those background regions not visible during the training period. Lastly, our approach is extended for handling ghost detection. The proposed method obtains very accurate and robust motionsegmentation results in multiple indoor and outdoor scenarios, while outperforming the most-referred state-of-art approaches. |
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| Publisher |
Elsevier |
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ISE |
Approved |
no |
| Call Number |
Admin @ si @ HAR2013 |
Serial |
1808 |
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| Author |
Fadi Dornaika; Angel Sappa |
| Title |
Instantaneous 3D motion from image derivatives using the Least Trimmed Square Regression |
Type |
Journal Article |
| Year |
2009 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
| Volume |
30 |
Issue |
5 |
Pages |
535–543 |
| Keywords |
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| Abstract |
This paper presents a new technique to the instantaneous 3D motion estimation. The main contributions are as follows. First, we show that the 3D camera or scene velocity can be retrieved from image derivatives only assuming that the scene contains a dominant plane. Second, we propose a new robust algorithm that simultaneously provides the Least Trimmed Square solution and the percentage of inliers-the non-contaminated data. Experiments on both synthetic and real image sequences demonstrated the effectiveness of the developed method. Those experiments show that the new robust approach can outperform classical robust schemes. |
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| Publisher |
Elsevier Science Inc. |
Place of Publication |
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Edition |
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| ISSN |
0167-8655 |
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| Notes |
ADAS |
Approved |
no |
| Call Number |
ADAS @ adas @ DoS2009a |
Serial |
1115 |
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| Author |
Lluis Gomez; Ali Furkan Biten; Ruben Tito; Andres Mafla; Marçal Rusiñol; Ernest Valveny; Dimosthenis Karatzas |
| Title |
Multimodal grid features and cell pointers for scene text visual question answering |
Type |
Journal Article |
| Year |
2021 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
| Volume |
150 |
Issue |
|
Pages |
242-249 |
| Keywords |
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| Abstract |
This paper presents a new model for the task of scene text visual question answering. In this task questions about a given image can only be answered by reading and understanding scene text. Current state of the art models for this task make use of a dual attention mechanism in which one attention module attends to visual features while the other attends to textual features. A possible issue with this is that it makes difficult for the model to reason jointly about both modalities. To fix this problem we propose a new model that is based on an single attention mechanism that attends to multi-modal features conditioned to the question. The output weights of this attention module over a grid of multi-modal spatial features are interpreted as the probability that a certain spatial location of the image contains the answer text to the given question. Our experiments demonstrate competitive performance in two standard datasets with a model that is faster than previous methods at inference time. Furthermore, we also provide a novel analysis of the ST-VQA dataset based on a human performance study. Supplementary material, code, and data is made available through this link. |
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Conference |
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| Notes |
DAG; 600.084; 600.121 |
Approved |
no |
| Call Number |
Admin @ si @ GBT2021 |
Serial |
3620 |
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| Author |
Jon Almazan; Ernest Valveny; Alicia Fornes |
| Title |
Deforming the Blurred Shape Model for Shape Description and Recognition |
Type |
Conference Article |
| Year |
2011 |
Publication |
5th Iberian Conference on Pattern Recognition and Image Analysis |
Abbreviated Journal |
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| Volume |
6669 |
Issue |
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Pages |
1-8 |
| Keywords |
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| Abstract |
This paper presents a new model for the description and recognition of distorted shapes, where the image is represented by a pixel density distribution based on the Blurred Shape Model combined with a non-linear image deformation model. This leads to an adaptive structure able to capture elastic deformations in shapes. This method has been evaluated using thee different datasets where deformations are present, showing the robustness and good performance of the new model. Moreover, we show that incorporating deformation and flexibility, the new model outperforms the BSM approach when classifying shapes with high variability of appearance. |
| Address |
Las Palmas de Gran Canaria. Spain |
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Thesis |
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| Publisher |
Springer-Verlag |
Place of Publication |
Berlin |
Editor |
Jordi Vitria; Joao Miguel Raposo; Mario Hernandez |
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Summary Language |
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Original Title |
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LNCS |
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Conference |
IbPRIA |
| Notes |
DAG; |
Approved |
no |
| Call Number |
Admin @ si @ AVF2011 |
Serial |
1732 |
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| Author |
Fadi Dornaika; Bogdan Raducanu |
| Title |
Person-specific face shape estimation under varying head pose from single snapshots |
Type |
Conference Article |
| Year |
2010 |
Publication |
20th International Conference on Pattern Recognition |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
3496–3499 |
| Keywords |
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| Abstract |
This paper presents a new method for person-specific face shape estimation under varying head pose of a previously unseen person from a single image. We describe a featureless approach based on a deformable 3D model and a learned face subspace. The proposed approach is based on maximizing a likelihood measure associated with a learned face subspace, which is carried out by a stochastic and genetic optimizer. We conducted the experiments on a subset of Honda Video Database showing the feasibility and robustness of the proposed approach. For this reason, our approach could lend itself nicely to complex frameworks involving 3D face tracking and face gesture recognition in monocular videos. |
| Address |
Istanbul, Turkey |
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Series Issue |
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Edition |
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| ISSN |
1051-4651 |
ISBN |
978-1-4244-7542-1 |
Medium |
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Expedition |
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Conference |
ICPR |
| Notes |
OR;MV |
Approved |
no |
| Call Number |
BCNPCL @ bcnpcl @ DoR2010b |
Serial |
1361 |
| Permanent link to this record |
