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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 |
Type |
Conference Article |
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Year |
2011 |
Publication |
IEEE International Conference on Computer Vision – Workshops |
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Pages |
2042-2049 |
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IEEE International Conference on Computer Vision – Workshops |
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Abstract |
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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ICCVW |
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Notes ![sorted by Notes field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
IAM; ADAS |
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no |
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IAM @ iam @ MGH2011 |
Serial |
1682 |
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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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185-206 |
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Intech |
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Yasuhiro Honda |
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English |
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english |
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978-953-307-900-4 |
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Notes ![sorted by Notes field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
IAM; ADAS |
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no |
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Call Number |
IAM @ iam @ HeG2012 |
Serial |
1684 |
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Author |
Patricia Marquez; Debora Gil; Aura Hernandez-Sabate |
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Title |
Evaluation of the Capabilities of Confidence Measures for Assessing Optical Flow Quality |
Type |
Conference Article |
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Year |
2013 |
Publication |
ICCV Workshop on Computer Vision in Vehicle Technology: From Earth to Mars |
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624-631 |
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Assessing Optical Flow (OF) quality is essential for its further use in reliable decision support systems. The absence of ground truth in such situations leads to the computation of OF Confidence Measures (CM) obtained from either input or output data. A fair comparison across the capabilities of the different CM for bounding OF error is required in order to choose the best OF-CM pair for discarding points where OF computation is not reliable. This paper presents a statistical probabilistic framework for assessing the quality of a given CM. Our quality measure is given in terms of the percentage of pixels whose OF error bound can not be determined by CM values. We also provide statistical tools for the computation of CM values that ensures a given accuracy of the flow field. |
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Sydney; Australia; December 2013 |
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CVTT:E2M |
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Notes ![sorted by Notes field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
IAM; ADAS; 600.044; 600.057; 601.145 |
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no |
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Call Number |
Admin @ si @ MGH2013b |
Serial |
2351 |
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Author |
Patricia Marquez; Debora Gil; R.Mester; Aura Hernandez-Sabate |
![download PDF file pdf](http://refbase.cvc.uab.es/img/file_PDF.gif)
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Title |
Local Analysis of Confidence Measures for Optical Flow Quality Evaluation |
Type |
Conference Article |
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Year |
2014 |
Publication |
9th International Conference on Computer Vision Theory and Applications |
Abbreviated Journal |
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Volume |
3 |
Issue |
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Pages |
450-457 |
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Keywords |
Optical Flow; Confidence Measure; Performance Evaluation. |
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Abstract |
Optical Flow (OF) techniques facing the complexity of real sequences have been developed in the last years. Even using the most appropriate technique for our specific problem, at some points the output flow might fail to achieve the minimum error required for the system. Confidence measures computed from either input data or OF output should discard those points where OF is not accurate enough for its further use. It follows that evaluating the capabilities of a confidence measure for bounding OF error is as important as the definition
itself. In this paper we analyze different confidence measures and point out their advantages and limitations for their use in real world settings. We also explore the agreement with current tools for their evaluation of confidence measures performance. |
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Lisboa; January 2014 |
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VISAPP |
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Notes ![sorted by Notes field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
IAM; ADAS; 600.044; 600.060; 600.057; 601.145; 600.076; 600.075 |
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no |
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Call Number |
Admin @ si @ MGM2014 |
Serial |
2432 |
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Author |
Patricia Marquez; H. Kause; A. Fuster; Aura Hernandez-Sabate; L. Florack; Debora Gil; Hans van Assen |
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Title |
Factors Affecting Optical Flow Performance in Tagging Magnetic Resonance Imaging |
Type |
Conference Article |
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Year |
2014 |
Publication |
17th International Conference on Medical Image Computing and Computer Assisted Intervention |
Abbreviated Journal |
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Volume |
8896 |
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Pages |
231-238 |
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Keywords |
Optical flow; Performance Evaluation; Synthetic Database; ANOVA; Tagging Magnetic Resonance Imaging |
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Abstract |
Changes in cardiac deformation patterns are correlated with cardiac pathologies. Deformation can be extracted from tagging Magnetic Resonance Imaging (tMRI) using Optical Flow (OF) techniques. For applications of OF in a clinical setting it is important to assess to what extent the performance of a particular OF method is stable across dierent clinical acquisition artifacts. This paper presents a statistical validation framework, based on ANOVA, to assess the motion and appearance factors that have the largest in uence on OF accuracy drop.
In order to validate this framework, we created a database of simulated tMRI data including the most common artifacts of MRI and test three dierent OF methods, including HARP. |
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Address |
Boston; USA; September 2014 |
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Springer International Publishing |
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LNCS |
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0302-9743 |
ISBN |
978-3-319-14677-5 |
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STACOM |
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Notes ![sorted by Notes field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
IAM; ADAS; 600.060; 601.145; 600.076; 600.075 |
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no |
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Call Number |
Admin @ si @ MKF2014 |
Serial |
2495 |
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Author |
Enric Marti; Antoni Gurgui; Debora Gil; Aura Hernandez-Sabate; Jaume Rocarias; Ferran Poveda |
![download PDF file pdf](http://refbase.cvc.uab.es/img/file_PDF.gif)
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Title |
ABP on line: Seguimiento, estregas y evaluación en aprendizaje basado en proyectos |
Type |
Miscellaneous |
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Year |
2014 |
Publication |
8th International Congress on University Teaching and Innovation |
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Tarragona; juliol 2014 |
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CIDUI |
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Notes ![sorted by Notes field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
IAM; ADAS; 600.076; 600.063; 600.075 |
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no |
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Admin @ si @ MGG2014 |
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2457 |
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Author |
Enric Marti; J.Roncaries; Debora Gil; Aura Hernandez-Sabate; Antoni Gurgui; Ferran Poveda |
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Title |
PBL On Line: A proposal for the organization, part-time monitoring and assessment of PBL group activities |
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Journal |
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Year |
2015 |
Publication |
Journal of Technology and Science Education |
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JOTSE |
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Volume |
5 |
Issue |
2 |
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87-96 |
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Notes ![sorted by Notes field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
IAM; ADAS; 600.076; 600.075 |
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no |
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Admin @ si @ MRG2015 |
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2608 |
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Author |
Hanne Kause; Patricia Marquez; Andrea Fuster; Aura Hernandez-Sabate; Luc Florack; Debora Gil; Hans van Assen |
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Title |
Quality Assessment of Optical Flow in Tagging MRI |
Type |
Conference Article |
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2015 |
Publication |
5th Dutch Bio-Medical Engineering Conference BME2015 |
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The Netherlands; January 2015 |
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BME |
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Notes ![sorted by Notes field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
IAM; ADAS; 600.076; 600.075 |
Approved |
no |
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Admin @ si @ KMF2015 |
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2616 |
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Permanent link to this record |
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Author |
Aura Hernandez-Sabate; Jose Elias Yauri; Pau Folch; Miquel Angel Piera; Debora Gil |
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Title |
Recognition of the Mental Workloads of Pilots in the Cockpit Using EEG Signals |
Type |
Journal Article |
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Year |
2022 |
Publication |
Applied Sciences |
Abbreviated Journal |
APPLSCI |
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Volume |
12 |
Issue |
5 |
Pages |
2298 |
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Keywords |
Cognitive states; Mental workload; EEG analysis; Neural networks; Multimodal data fusion |
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Abstract |
The commercial flightdeck is a naturally multi-tasking work environment, one in which interruptions are frequent come in various forms, contributing in many cases to aviation incident reports. Automatic characterization of pilots’ workloads is essential to preventing these kind of incidents. In addition, minimizing the physiological sensor network as much as possible remains both a challenge and a requirement. Electroencephalogram (EEG) signals have shown high correlations with specific cognitive and mental states, such as workload. However, there is not enough evidence in the literature to validate how well models generalize in cases of new subjects performing tasks with workloads similar to the ones included during the model’s training. In this paper, we propose a convolutional neural network to classify EEG features across different mental workloads in a continuous performance task test that partly measures working memory and working memory capacity. Our model is valid at the general population level and it is able to transfer task learning to pilot mental workload recognition in a simulated operational environment. |
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February 2022 |
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Notes ![sorted by Notes field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
IAM; ADAS; 600.139; 600.145; 600.118 |
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Admin @ si @ HYF2022 |
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3720 |
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Author |
Francesco Brughi; Debora Gil; Llorenç Badiella; Eva Jove Casabella; Oriol Ramos Terrades |
![download PDF file pdf](http://refbase.cvc.uab.es/img/file_PDF.gif)
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Title |
Exploring the impact of inter-query variability on the performance of retrieval systems |
Type |
Conference Article |
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Year |
2014 |
Publication |
11th International Conference on Image Analysis and Recognition |
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8814 |
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413–420 |
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This paper introduces a framework for evaluating the performance of information retrieval systems. Current evaluation metrics provide an average score that does not consider performance variability across the query set. In this manner, conclusions lack of any statistical significance, yielding poor inference to cases outside the query set and possibly unfair comparisons. We propose to apply statistical methods in order to obtain a more informative measure for problems in which different query classes can be identified. In this context, we assess the performance variability on two levels: overall variability across the whole query set and specific query class-related variability. To this end, we estimate confidence bands for precision-recall curves, and we apply ANOVA in order to assess the significance of the performance across different query classes. |
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Algarve; Portugal; October 2014 |
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Springer International Publishing |
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0302-9743 |
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978-3-319-11757-7 |
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ICIAR |
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Notes ![sorted by Notes field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
IAM; DAG; 600.060; 600.061; 600.077; 600.075 |
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Admin @ si @ BGB2014 |
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2559 |
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