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| Author | Hugo Bertiche; Meysam Madadi; Sergio Escalera | ||||
| Title | PBNS: Physically Based Neural Simulation for Unsupervised Garment Pose Space Deformation | Type | Journal Article | ||
| Year | 2021 | Publication | ACM Transactions on Graphics | Abbreviated Journal | |
| Volume | 40 | Issue  |
6 | Pages | 1-14 |
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| Abstract | We present a methodology to automatically obtain Pose Space Deformation (PSD) basis for rigged garments through deep learning. Classical approaches rely on Physically Based Simulations (PBS) to animate clothes. These are general solutions that, given a sufficiently fine-grained discretization of space and time, can achieve highly realistic results. However, they are computationally expensive and any scene modification prompts the need of re-simulation. Linear Blend Skinning (LBS) with PSD offers a lightweight alternative to PBS, though, it needs huge volumes of data to learn proper PSD. We propose using deep learning, formulated as an implicit PBS, to unsupervisedly learn realistic cloth Pose Space Deformations in a constrained scenario: dressed humans. Furthermore, we show it is possible to train these models in an amount of time comparable to a PBS of a few sequences. To the best of our knowledge, we are the first to propose a neural simulator for cloth.
While deep-based approaches in the domain are becoming a trend, these are data-hungry models. Moreover, authors often propose complex formulations to better learn wrinkles from PBS data. Supervised learning leads to physically inconsistent predictions that require collision solving to be used. Also, dependency on PBS data limits the scalability of these solutions, while their formulation hinders its applicability and compatibility. By proposing an unsupervised methodology to learn PSD for LBS models (3D animation standard), we overcome both of these drawbacks. Results obtained show cloth-consistency in the animated garments and meaningful pose-dependant folds and wrinkles. Our solution is extremely efficient, handles multiple layers of cloth, allows unsupervised outfit resizing and can be easily applied to any custom 3D avatar. |
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| Notes | HUPBA; no proj | Approved | no | ||
| Call Number | Admin @ si @ BME2021c | Serial | 3643 | ||
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| Author | AN Ruchai; VI Kober; KA Dorofeev; VN Karnaukhov; Mikhail Mozerov | ||||
| Title | Classification of breast abnormalities using a deep convolutional neural network and transfer learning | Type | Journal Article | ||
| Year | 2021 | Publication | Journal of Communications Technology and Electronics | Abbreviated Journal | |
| Volume | 66 | Issue |
6 | Pages | 778–783 |
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| Abstract | A new algorithm for classification of breast pathologies in digital mammography using a convolutional neural network and transfer learning is proposed. The following pretrained neural networks were chosen: MobileNetV2, InceptionResNetV2, Xception, and ResNetV2. All mammographic images were pre-processed to improve classification reliability. Transfer training was carried out using additional data augmentation and fine-tuning. The performance of the proposed algorithm for classification of breast pathologies in terms of accuracy on real data is discussed and compared with that of state-of-the-art algorithms on the available MIAS database. | ||||
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| Notes | LAMP; | Approved | no | ||
| Call Number | Admin @ si @ RKD2022 | Serial | 3680 | ||
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| Author | Rafael E. Rivadeneira; Angel Sappa; Boris X. Vintimilla; Riad I. Hammoud | ||||
| Title | A Novel Domain Transfer-Based Approach for Unsupervised Thermal Image Super-Resolution | Type | Journal Article | ||
| Year | 2022 | Publication | Sensors | Abbreviated Journal | SENS |
| Volume | 22 | Issue |
6 | Pages | 2254 |
| Keywords | Thermal image super-resolution; unsupervised super-resolution; thermal images; attention module; semiregistered thermal images | ||||
| Abstract | This paper presents a transfer domain strategy to tackle the limitations of low-resolution thermal sensors and generate higher-resolution images of reasonable quality. The proposed technique employs a CycleGAN architecture and uses a ResNet as an encoder in the generator along with an attention module and a novel loss function. The network is trained on a multi-resolution thermal image dataset acquired with three different thermal sensors. Results report better performance benchmarking results on the 2nd CVPR-PBVS-2021 thermal image super-resolution challenge than state-of-the-art methods. The code of this work is available online. | ||||
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| Notes | MSIAU; | Approved | no | ||
| Call Number | Admin @ si @ RSV2022b | Serial | 3688 | ||
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| Author | Hugo Bertiche; Meysam Madadi; Sergio Escalera | ||||
| Title | Neural Cloth Simulation | Type | Journal Article | ||
| Year | 2022 | Publication | ACM Transactions on Graphics | Abbreviated Journal | ACMTGraph |
| Volume | 41 | Issue |
6 | Pages | 1-14 |
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| Abstract | We present a general framework for the garment animation problem through unsupervised deep learning inspired in physically based simulation. Existing trends in the literature already explore this possibility. Nonetheless, these approaches do not handle cloth dynamics. Here, we propose the first methodology able to learn realistic cloth dynamics unsupervisedly, and henceforth, a general formulation for neural cloth simulation. The key to achieve this is to adapt an existing optimization scheme for motion from simulation based methodologies to deep learning. Then, analyzing the nature of the problem, we devise an architecture able to automatically disentangle static and dynamic cloth subspaces by design. We will show how this improves model performance. Additionally, this opens the possibility of a novel motion augmentation technique that greatly improves generalization. Finally, we show it also allows to control the level of motion in the predictions. This is a useful, never seen before, tool for artists. We provide of detailed analysis of the problem to establish the bases of neural cloth simulation and guide future research into the specifics of this domain.
ACM Transactions on GraphicsVolume 41Issue 6December 2022 Article No.: 220pp 1– |
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| Address | Dec 2022 | ||||
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| Publisher | ACM | Place of Publication | Editor | ||
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| Notes | Approved | no | |||
| Call Number | Admin @ si @ BME2022b | Serial | 3779 | ||
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| Author | Marçal Rusiñol; Lluis Pere de las Heras; Oriol Ramos Terrades | ||||
| Title | Flowchart Recognition for Non-Textual Information Retrieval in Patent Search | Type | Journal Article | ||
| Year | 2014 | Publication | Information Retrieval | Abbreviated Journal | IR |
| Volume | 17 | Issue |
5-6 | Pages | 545-562 |
| Keywords | Flowchart recognition; Patent documents; Text/graphics separation; Raster-to-vector conversion; Symbol recognition | ||||
| Abstract | Relatively little research has been done on the topic of patent image retrieval and in general in most of the approaches the retrieval is performed in terms of a similarity measure between the query image and the images in the corpus. However, systems aimed at overcoming the semantic gap between the visual description of patent images and their conveyed concepts would be very helpful for patent professionals. In this paper we present a flowchart recognition method aimed at achieving a structured representation of flowchart images that can be further queried semantically. The proposed method was submitted to the CLEF-IP 2012 flowchart recognition task. We report the obtained results on this dataset. | ||||
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| ISSN | 1386-4564 | ISBN | Medium | ||
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| Notes | DAG; 600.077 | Approved | no | ||
| Call Number | Admin @ si @ RHR2013 | Serial | 2342 | ||
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| Author | D. Seron; F. Moreso; C. Gratin; Jordi Vitria; E. Condom | ||||
| Title | Automated classification of renal interstitium and tubules by local texture analysis and a neural network | Type | Journal Article | ||
| Year | 1996 | Publication | Analytical and Quantitative Cytology and Histology | Abbreviated Journal | |
| Volume | 18 | Issue |
5 | Pages | 410-9, PMID: 8908314 |
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| Notes | OR;MV | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ SMG1996 | Serial | 76 | ||
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| Author | Felipe Lumbreras; Joan Serrat | ||||
| Title | Segmentation of petrographical images of marbles | Type | Journal Article | ||
| Year | 1996 | Publication | Computers and Geosciences | Abbreviated Journal | |
| Volume | 22 | Issue |
5 | Pages | 547–558 |
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| Notes | ADAS | Approved | no | ||
| Call Number | ADAS @ adas @ LuS1996b | Serial | 82 | ||
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| Author | Joan Serrat; Ferran Diego; Felipe Lumbreras; Jose Manuel Alvarez; Antonio Lopez; C. Elvira | ||||
| Title | Dynamic Comparison of Headlights | Type | Journal Article | ||
| Year | 2008 | Publication | Journal of Automobile Engineering | Abbreviated Journal | |
| Volume | 222 | Issue |
5 | Pages | 643–656 |
| Keywords | video alignment | ||||
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| Notes | ADAS | Approved | no | ||
| Call Number | ADAS @ adas @ SDL2008a | Serial | 958 | ||
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| Author | C. Butakoff; Simone Balocco; F.M. Sukno; C. Hoogendoorn; C. Tobon-Gomez; G. Avegliano; A.F. Frangi | ||||
| Title | Left-ventricular Epi- and Endocardium Extraction from 3D Ultrasound Images Using an Automatically Constructed 3D ASM | Type | Journal Article | ||
| Year | 2016 | Publication | Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization | Abbreviated Journal | CMBBE |
| Volume | 4 | Issue |
5 | Pages | 265-280 |
| Keywords | ASM; cardiac segmentation; statistical model; shape model; 3D ultrasound; cardiac segmentation | ||||
| Abstract | In this paper, we propose an automatic method for constructing an active shape model (ASM) to segment the complete cardiac left ventricle in 3D ultrasound (3DUS) images, which avoids costly manual landmarking. The automatic construction of the ASM has already been addressed in the literature; however, the direct application of these methods to 3DUS is hampered by a high level of noise and artefacts. Therefore, we propose to construct the ASM by fusing the multidetector computed tomography data, to learn the shape, with the artificially generated 3DUS, in order to learn the neighbourhood of the boundaries. Our artificial images were generated by two approaches: a faster one that does not take into account the geometry of the transducer, and a more comprehensive one, implemented in Field II toolbox. The segmentation accuracy of our ASM was evaluated on 20 patients with left-ventricular asynchrony, demonstrating plausibility of the approach. | ||||
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| ISSN | 2168-1163 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | MILAB | Approved | no | ||
| Call Number | Admin @ si @ BBS2016 | Serial | 2449 | ||
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| Author | Miquel Ferrer; Ernest Valveny; F. Serratosa | ||||
| Title | Median graph: A new exact algorithm using a distance based on the maximum common subgraph | Type | Journal Article | ||
| Year | 2009 | Publication | Pattern Recognition Letters | Abbreviated Journal | PRL |
| Volume | 30 | Issue |
5 | Pages | 579–588 |
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| Abstract | Median graphs have been presented as a useful tool for capturing the essential information of a set of graphs. Nevertheless, computation of optimal solutions is a very hard problem. In this work we present a new and more efficient optimal algorithm for the median graph computation. With the use of a particular cost function that permits the definition of the graph edit distance in terms of the maximum common subgraph, and a prediction function in the backtracking algorithm, we reduce the size of the search space, avoiding the evaluation of a great amount of states and still obtaining the exact median. We present a set of experiments comparing our new algorithm against the previous existing exact algorithm using synthetic data. In addition, we present the first application of the exact median graph computation to real data and we compare the results against an approximate algorithm based on genetic search. These experimental results show that our algorithm outperforms the previous existing exact algorithm and in addition show the potential applicability of the exact solutions to real problems. | ||||
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| Publisher | Elsevier Science Inc. | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 0167-8655 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | DAG | Approved | no | ||
| Call Number | DAG @ dag @ FVS2009a | Serial | 1114 | ||
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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 |
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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 | Editor | ||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 0167-8655 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | ADAS | Approved | no | ||
| Call Number | ADAS @ adas @ DoS2009a | Serial | 1115 | ||
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| Author | David Geronimo; Angel Sappa; Daniel Ponsa; Antonio Lopez | ||||
| Title | 2D-3D based on-board pedestrian detection system | Type | Journal Article | ||
| Year | 2010 | Publication | Computer Vision and Image Understanding | Abbreviated Journal | CVIU |
| Volume | 114 | Issue |
5 | Pages | 583–595 |
| Keywords | Pedestrian detection; Advanced Driver Assistance Systems; Horizon line; Haar wavelets; Edge orientation histograms | ||||
| Abstract | During the next decade, on-board pedestrian detection systems will play a key role in the challenge of increasing traffic safety. The main target of these systems, to detect pedestrians in urban scenarios, implies overcoming difficulties like processing outdoor scenes from a mobile platform and searching for aspect-changing objects in cluttered environments. This makes such systems combine techniques in the state-of-the-art Computer Vision. In this paper we present a three module system based on both 2D and 3D cues. The first module uses 3D information to estimate the road plane parameters and thus select a coherent set of regions of interest (ROIs) to be further analyzed. The second module uses Real AdaBoost and a combined set of Haar wavelets and edge orientation histograms to classify the incoming ROIs as pedestrian or non-pedestrian. The final module loops again with the 3D cue in order to verify the classified ROIs and with the 2D in order to refine the final results. According to the results, the integration of the proposed techniques gives rise to a promising system. | ||||
| Address | Computer Vision and Image Understanding (Special Issue on Intelligent Vision Systems), Vol. 114(5):583-595 | ||||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1077-3142 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | ADAS | Approved | no | ||
| Call Number | ADAS @ adas @ GSP2010 | Serial | 1341 | ||
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| Author | Debora Gil; Oriol Rodriguez-Leor; Petia Radeva; J. Mauri | ||||
| Title | Myocardial Perfusion Characterization From Contrast Angiography Spectral Distribution | Type | Journal Article | ||
| Year | 2008 | Publication | IEEE Transactions on Medical Imaging | Abbreviated Journal | |
| Volume | 27 | Issue |
5 | Pages | 641-649 |
| Keywords | Contrast angiography; myocardial perfusion; spectral analysis. | ||||
| Abstract | Despite recovering a normal coronary flow after acute myocardial infarction, percutaneous coronary intervention does not guarantee a proper perfusion (irrigation) of the infarcted area. This damage in microcirculation integrity may detrimentally affect the patient survival. Visual assessment of the myocardium opacification in contrast angiography serves to define a subjective score of the microcirculation integrity myocardial blush analysis (MBA). Although MBA correlates with patient prognosis its visual assessment is a very difficult task that requires of a highly expertise training in order to achieve a good intraobserver and interobserver agreement. In this paper, we provide objective descriptors of the myocardium staining pattern by analyzing the spectrum of the image local statistics. The descriptors proposed discriminate among the different phenomena observed in the angiographic sequence and allow defining an objective score of the myocardial perfusion. | ||||
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| Notes | IAM;MILAB | Approved | no | ||
| Call Number | IAM @ iam @ GRR2008 | Serial | 1541 | ||
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| Author | Pierluigi Casale; Oriol Pujol; Petia Radeva | ||||
| Title | Personalization and User Verification in Wearable Systems using Biometric Walking Patterns | Type | Journal Article | ||
| Year | 2012 | Publication | Personal and Ubiquitous Computing | Abbreviated Journal | PUC |
| Volume | 16 | Issue |
5 | Pages | 563-580 |
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| Abstract | In this article, a novel technique for user’s authentication and verification using gait as a biometric unobtrusive pattern is proposed. The method is based on a two stages pipeline. First, a general activity recognition classifier is personalized for an specific user using a small sample of her/his walking pattern. As a result, the system is much more selective with respect to the new walking pattern. A second stage verifies whether the user is an authorized one or not. This stage is defined as a one-class classification problem. In order to solve this problem, a four-layer architecture is built around the geometric concept of convex hull. This architecture allows to improve robustness to outliers, modeling non-convex shapes, and to take into account temporal coherence information. Two different scenarios are proposed as validation with two different wearable systems. First, a custom high-performance wearable system is built and used in a free environment. A second dataset is acquired from an Android-based commercial device in a ‘wild’ scenario with rough terrains, adversarial conditions, crowded places and obstacles. Results on both systems and datasets are very promising, reducing the verification error rates by an order of magnitude with respect to the state-of-the-art technologies. | ||||
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| Publisher | Springer-Verlag | Place of Publication | Editor | ||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1617-4909 | ISBN | Medium | ||
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| Notes | MILAB;HuPBA | Approved | no | ||
| Call Number | Admin @ si @ CPR2012 | Serial | 1706 | ||
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| Author | Jose Seabra; Francesco Ciompi; Oriol Pujol; J. Mauri; Petia Radeva; Joao Sanchez | ||||
| Title | Rayleigh Mixture Model for Plaque Characterization in Intravascular Ultrasound | Type | Journal Article | ||
| Year | 2011 | Publication | IEEE Transactions on Biomedical Engineering | Abbreviated Journal | TBME |
| Volume | 58 | Issue |
5 | Pages | 1314-1324 |
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| Abstract | Vulnerable plaques are the major cause of carotid and coronary vascular problems, such as heart attack or stroke. A correct modeling of plaque echomorphology and composition can help the identification of such lesions. The Rayleigh distribution is widely used to describe (nearly) homogeneous areas in ultrasound images. Since plaques may contain tissues with heterogeneous regions, more complex distributions depending on multiple parameters are usually needed, such as Rice, K or Nakagami distributions. In such cases, the problem formulation becomes more complex, and the optimization procedure to estimate the plaque echomorphology is more difficult. Here, we propose to model the tissue echomorphology by means of a mixture of Rayleigh distributions, known as the Rayleigh mixture model (RMM). The problem formulation is still simple, but its ability to describe complex textural patterns is very powerful. In this paper, we present a method for the automatic estimation of the RMM mixture parameters by means of the expectation maximization algorithm, which aims at characterizing tissue echomorphology in ultrasound (US). The performance of the proposed model is evaluated with a database of in vitro intravascular US cases. We show that the mixture coefficients and Rayleigh parameters explicitly derived from the mixture model are able to accurately describe different plaque types and to significantly improve the characterization performance of an already existing methodology. | ||||
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| Notes | MILAB;HuPBA | Approved | no | ||
| Call Number | Admin @ si @ SCP2011 | Serial | 1712 | ||
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