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Author |
Debora Gil; Petia Radeva |
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Title |
A Regularized Curvature Flow Designed for a Selective Shape Restoration |
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Journal Article |
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2004 |
Publication ![sorted by Publication field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
IEEE Transactions on Image Processing |
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13 |
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1444–1458 |
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Geometric flows, nonlinear filtering, shape recovery. |
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Among all filtering techniques, those based exclu- sively on image level sets (geometric flows) have proven to be the less sensitive to the nature of noise and the most contrast preserving. A common feature to existent curvature flows is that they penalize high curvature, regardless of the curve regularity. This constitutes a major drawback since curvature extreme values are standard descriptors of the contour geometry. We argue that an operator designed with shape recovery purposes should include a term penalizing irregularity in the curvature rather than its magnitude. To this purpose, we present a novel geometric flow that includes a function that measures the degree of local irregularity present in the curve. A main advantage is that it achieves non-trivial steady states representing a smooth model of level curves in a noisy image. Performance of our approach is compared to classical filtering techniques in terms of quality in the restored image/shape and asymptotic behavior. We empirically prove that our approach is the technique that achieves the best compromise between image quality and evolution stabilization. |
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IAM;MILAB |
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BCNPCL @ bcnpcl @ GiR2004b |
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491 |
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Author |
Debora Gil; Guillermo Torres; Carles Sanchez |
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Title |
Transforming radiomic features into radiological words |
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Conference Article |
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2023 |
Publication ![sorted by Publication field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
IEEE International Symposium on Biomedical Imaging |
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Cartagena de Indias; Colombia; April 2023 |
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ISBI |
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IAM |
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Admin @ si @ GTS2023 |
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3952 |
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Author |
Pau Cano; Debora Gil; Eva Musulen |
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Title |
Towards automatic detection of helicobacter pylori in histological samples of gastric tissue |
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2023 |
Publication ![sorted by Publication field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
IEEE International Symposium on Biomedical Imaging |
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Cartagena de Indias; Colombia; April 2023 |
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ISBI |
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IAM |
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Admin @ si @ CGM2023 |
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3953 |
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Author |
Guillermo Torres; Debora Gil; Antonio Rosell; Sonia Baeza; Carles Sanchez |
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Title |
A radiomic biopsy for virtual histology of pulmonary nodules |
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Conference Article |
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2023 |
Publication ![sorted by Publication field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
IEEE International Symposium on Biomedical Imaging |
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Cartagena de Indias; Colombia; April 2023 |
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ISBI |
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IAM |
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Admin @ si @ TGR2023b |
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3954 |
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Author |
Patricia Marquez; Debora Gil; Aura Hernandez-Sabate |
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Title |
A Confidence Measure for Assessing Optical Flow Accuracy in the Absence of Ground Truth |
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Conference Article |
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2011 |
Publication ![sorted by Publication field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
IEEE International Conference on Computer Vision – Workshops |
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2042-2049 |
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IEEE International Conference on Computer Vision – Workshops |
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Optical flow is a valuable tool for motion analysis in autonomous navigation systems. A reliable application requires determining the accuracy of the computed optical flow. This is a main challenge given the absence of ground truth in real world sequences. This paper introduces a measure of optical flow accuracy for Lucas-Kanade based flows in terms of the numerical stability of the data-term. We call this measure optical flow condition number. A statistical analysis over ground-truth data show a good statistical correlation between the condition number and optical flow error. Experiments on driving sequences illustrate its potential for autonomous navigation systems. |
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IEEE |
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Barcelona (Spain) |
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English |
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English |
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ICCVW |
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IAM; ADAS |
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IAM @ iam @ MGH2011 |
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1682 |
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Permanent link to this record |
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Author |
Katerine Diaz; Jesus Martinez del Rincon; Aura Hernandez-Sabate; Debora Gil |
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Title |
Continuous head pose estimation using manifold subspace embedding and multivariate regression |
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Journal Article |
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2018 |
Publication ![sorted by Publication field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
IEEE Access |
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ACCESS |
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6 |
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18325 - 18334 |
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Head Pose estimation; HOG features; Generalized Discriminative Common Vectors; B-splines; Multiple linear regression |
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In this paper, a continuous head pose estimation system is proposed to estimate yaw and pitch head angles from raw facial images. Our approach is based on manifold learningbased methods, due to their promising generalization properties shown for face modelling from images. The method combines histograms of oriented gradients, generalized discriminative common vectors and continuous local regression to achieve successful performance. Our proposal was tested on multiple standard face datasets, as well as in a realistic scenario. Results show a considerable performance improvement and a higher consistence of our model in comparison with other state-of-art methods, with angular errors varying between 9 and 17 degrees. |
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2169-3536 |
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ADAS; 600.118 |
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no |
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Admin @ si @ DMH2018b |
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3091 |
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Author |
Debora Gil; Antonio Esteban Lansaque; Agnes Borras; Esmitt Ramirez; Carles Sanchez |
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Title |
Intraoperative Extraction of Airways Anatomy in VideoBronchoscopy |
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Journal Article |
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2020 |
Publication ![sorted by Publication field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
IEEE Access |
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ACCESS |
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8 |
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159696 - 159704 |
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A main bottleneck in bronchoscopic biopsy sampling is to efficiently reach the lesion navigating across bronchial levels. Any guidance system should be able to localize the scope position during the intervention with minimal costs and alteration of clinical protocols. With the final goal of an affordable image-based guidance, this work presents a novel strategy to extract and codify the anatomical structure of bronchi, as well as, the scope navigation path from videobronchoscopy. Experiments using interventional data show that our method accurately identifies the bronchial structure. Meanwhile, experiments using simulated data verify that the extracted navigation path matches the 3D route. |
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IAM; 600.139; 600.145 |
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Admin @ si @ GEB2020 |
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3467 |
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Permanent link to this record |
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Author |
Miquel Angel Piera; Jose Luis Muñoz; Debora Gil; Gonzalo Martin; Jordi Manzano |
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Title |
A Socio-Technical Simulation Model for the Design of the Future Single Pilot Cockpit: An Opportunity to Improve Pilot Performance |
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Journal Article |
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2022 |
Publication ![sorted by Publication field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
IEEE Access |
Abbreviated Journal |
ACCESS |
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10 |
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22330-22343 |
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Human factors ; Performance evaluation ; Simulation; Sociotechnical systems ; System performance |
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The future deployment of single pilot operations must be supported by new cockpit computer services. Such services require an adaptive context-aware integration of technical functionalities with the concurrent tasks that a pilot must deal with. Advanced artificial intelligence supporting services and improved communication capabilities are the key enabling technologies that will render future cockpits more integrated with the present digitalized air traffic management system. However, an issue in the integration of such technologies is the lack of socio-technical analysis in the design of these teaming mechanisms. A key factor in determining how and when a service support should be provided is the dynamic evolution of pilot workload. This paper investigates how the socio-technical model-based systems engineering approach paves the way for the design of a digital assistant framework by formalizing this workload. The model was validated in an Airbus A-320 cockpit simulator, and the results confirmed the degraded pilot behavioral model and the performance impact according to different contextual flight deck information. This study contributes to practical knowledge for designing human-machine task-sharing systems. |
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Feb 2022 |
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IAM; |
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Admin @ si @ PMG2022 |
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3697 |
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Debora Gil; Aura Hernandez-Sabate; Julien Enconniere; Saryani Asmayawati; Pau Folch; Juan Borrego-Carazo; Miquel Angel Piera |
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Title |
E-Pilots: A System to Predict Hard Landing During the Approach Phase of Commercial Flights |
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Journal Article |
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2022 |
Publication ![sorted by Publication field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
IEEE Access |
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ACCESS |
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10 |
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7489-7503 |
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More than half of all commercial aircraft operation accidents could have been prevented by executing a go-around. Making timely decision to execute a go-around manoeuvre can potentially reduce overall aviation industry accident rate. In this paper, we describe a cockpit-deployable machine learning system to support flight crew go-around decision-making based on the prediction of a hard landing event.
This work presents a hybrid approach for hard landing prediction that uses features modelling temporal dependencies of aircraft variables as inputs to a neural network. Based on a large dataset of 58177 commercial flights, the results show that our approach has 85% of average sensitivity with 74% of average specificity at the go-around point. It follows that our approach is a cockpit-deployable recommendation system that outperforms existing approaches. |
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IAM; 600.139; 600.118; 600.145 |
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Admin @ si @ GHE2022 |
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3721 |
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Author |
David Castells; Vinh Ngo; Juan Borrego-Carazo; Marc Codina; Carles Sanchez; Debora Gil; Jordi Carrabina |
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Title |
A Survey of FPGA-Based Vision Systems for Autonomous Cars |
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Journal Article |
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2022 |
Publication ![sorted by Publication field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
IEEE Access |
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ACESS |
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10 |
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132525-132563 |
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Autonomous automobile; Computer vision; field programmable gate arrays; reconfigurable architectures |
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On the road to making self-driving cars a reality, academic and industrial researchers are working hard to continue to increase safety while meeting technical and regulatory constraints Understanding the surrounding environment is a fundamental task in self-driving cars. It requires combining complex computer vision algorithms. Although state-of-the-art algorithms achieve good accuracy, their implementations often require powerful computing platforms with high power consumption. In some cases, the processing speed does not meet real-time constraints. FPGA platforms are often used to implement a category of latency-critical algorithms that demand maximum performance and energy efficiency. Since self-driving car computer vision functions fall into this category, one could expect to see a wide adoption of FPGAs in autonomous cars. In this paper, we survey the computer vision FPGA-based works from the literature targeting automotive applications over the last decade. Based on the survey, we identify the strengths and weaknesses of FPGAs in this domain and future research opportunities and challenges. |
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16 December 2022 |
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IEEE |
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IAM; 600.166 |
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Admin @ si @ CNB2022 |
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3760 |
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