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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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Year |
2011 |
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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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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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English |
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ICCVW |
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IAM; ADAS |
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Call Number |
IAM @ iam @ MGH2011 |
Serial |
1682 |
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Author |
Patricia Marquez |
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Title |
A Confidence Framework for the Assessment of Optical Flow Performance |
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Book Whole |
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Year |
2015 |
Publication |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Optical Flow (OF) is the input of a wide range of decision support systems such as car driver assistance, UAV guiding or medical diagnose. In these real situations, the absence of ground truth forces to assess OF quality using quantities computed from either sequences or the computed optical flow itself. These quantities are generally known as Confidence Measures, CM. Even if we have a proper confidence measure we still need a way to evaluate its ability to discard pixels with an OF prone to have a large error. Current approaches only provide a descriptive evaluation of the CM performance but such approaches are not capable to fairly compare different confidence measures and optical flow algorithms. Thus, it is of prime importance to define a framework and a general road map for the evaluation of optical flow performance.
This thesis provides a framework able to decide which pairs “ optical flow – confidence measure” (OF-CM) are best suited for optical flow error bounding given a confidence level determined by a decision support system. To design this framework we cover the following points:
Descriptive scores. As a first step, we summarize and analyze the sources of inaccuracies in the output of optical flow algorithms. Second, we present several descriptive plots that visually assess CM capabilities for OF error bounding. In addition to the descriptive plots, given a plot representing OF-CM capabilities to bound the error, we provide a numeric score that categorizes the plot according to its decreasing profile, that is, a score assessing CM performance.
Statistical framework. We provide a comparison framework that assesses the best suited OF-CM pair for error bounding that uses a two stage cascade process. First of all we assess the predictive value of the confidence measures by means of a descriptive plot. Then, for a sample of descriptive plots computed over training frames, we obtain a generic curve that will be used for sequences with no ground truth. As a second step, we evaluate the obtained general curve and its capabilities to really reflect the predictive value of a confidence measure using the variability across train frames by means of ANOVA.
The presented framework has shown its potential in the application on clinical decision support systems. In particular, we have analyzed the impact of the different image artifacts such as noise and decay to the output of optical flow in a cardiac diagnose system and we have improved the navigation inside the bronchial tree on bronchoscopy. |
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July 2015 |
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Thesis |
Ph.D. thesis |
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Publisher |
Ediciones Graficas Rey |
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Debora Gil;Aura Hernandez |
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978-84-943427-2-1 |
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IAM; 600.075 |
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Call Number |
Admin @ si @ Mar2015 |
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2687 |
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Author |
Patricia Marquez;Debora Gil;Aura Hernandez-Sabate |
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Title |
A Complete Confidence Framework for Optical Flow |
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Conference Article |
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Year |
2012 |
Publication |
12th European Conference on Computer Vision – Workshops and Demonstrations |
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7584 |
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2 |
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124-133 |
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Keywords |
Optical flow, confidence measures, sparsification plots, error prediction plots |
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Medial representations are powerful tools for describing and parameterizing the volumetric shape of anatomical structures. Existing methods show excellent results when applied to 2D objects, but their quality drops across dimensions. This paper contributes to the computation of medial manifolds in two aspects. First, we provide a standard scheme for the computation of medial manifolds that avoid degenerated medial axis segments; second, we introduce an energy based method which performs independently of the dimension. We evaluate quantitatively the performance of our method with respect to existing approaches, by applying them to synthetic shapes of known medial geometry. Finally, we show results on shape representation of multiple abdominal organs, exploring the use of medial manifolds for the representation of multi-organ relations. |
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Springer-Verlag |
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Florence, Italy, October 7-13, 2012 |
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Andrea Fusiello, Vittorio Murino ,Rita Cucchiara |
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LNCS |
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978-3-642-33867-0 |
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ECCVW |
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IAM;ADAS; |
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IAM @ iam @ MGH2012b |
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1991 |
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Author |
Josep Llados; Ernest Valveny; Gemma Sanchez; Enric Marti |
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Title |
A Case Study of Pattern Recognition: Symbol Recognition in Graphic Documentsa |
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Conference Article |
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2003 |
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Proceedings of Pattern Recognition in Information Systems |
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1-13 |
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Angers, France |
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ICEIS Press |
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972-98816-3-4 |
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PRIS'03 |
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DAG;IAM; |
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IAM @ iam @ LVS2003 |
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1576 |
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Author |
Juan Borrego-Carazo; Carles Sanchez; David Castells; Jordi Carrabina; Debora Gil |
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Title |
A benchmark for the evaluation of computational methods for bronchoscopic navigation |
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Journal Article |
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Year |
2022 |
Publication |
International Journal of Computer Assisted Radiology and Surgery |
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IJCARS |
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17 |
Issue |
1 |
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IAM |
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Admin @ si @ BSC2022 |
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3832 |
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Author |
Debora Gil; F. Javier Sanchez; Gloria Fernandez Esparrach; Jorge Bernal |
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Title |
3D Stable Spatio-temporal Polyp Localization in Colonoscopy Videos |
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Book Chapter |
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Year |
2015 |
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Computer-Assisted and Robotic Endoscopy. Revised selected papers of Second International Workshop, CARE 2015, Held in Conjunction with MICCAI 2015 |
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9515 |
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140-152 |
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Colonoscopy, Polyp Detection, Polyp Localization, Region Extraction, Watersheds |
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Computational intelligent systems could reduce polyp miss rate in colonoscopy for colon cancer diagnosis and, thus, increase the efficiency of the procedure. One of the main problems of existing polyp localization methods is a lack of spatio-temporal stability in their response. We propose to explore the response of a given polyp localization across temporal windows in order to select
those image regions presenting the highest stable spatio-temporal response.
Spatio-temporal stability is achieved by extracting 3D watershed regions on the
temporal window. Stability in localization response is statistically determined by analysis of the variance of the output of the localization method inside each 3D region. We have explored the benefits of considering spatio-temporal stability in two different tasks: polyp localization and polyp detection. Experimental results indicate an average improvement of 21:5% in polyp localization and 43:78% in polyp detection. |
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CARE |
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IAM; MV; 600.075 |
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Admin @ si @ GSF2015 |
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2733 |
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Author |
Antonio Esteban Lansaque |
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Title |
3D reconstruction and recognition using structured ligth |
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Report |
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2014 |
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CVC Technical Report |
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179 |
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This work covers the problem of 3D reconstruction, recognition and 6DOF pose estimation. The goal of this project is to reconstruct a 3D scene and to align an object model of the industrial pieces onto the reconstructed scene. The reconstruction algorithm is based on stereo techniques and the recognition algorithm is based on SHOT descriptors computed on a set of uniform keypoints. Correspondences are used to estimate a first 6DOF transformation that maps the model onto the scene and then ICP algorithm is used to refine the transformation. In order to check the effectiveness of the proposed algorithm, several experiments were performed. These experiments were conducted on a lab environment in order to get results under the same conditions in all of them. Although obtained results are not real time results, the proposed algorithm ends up with high rates of object recognition. |
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UAB; September 2014 |
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Master's thesis |
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IAM; 600.075 |
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Call Number |
Admin @ si @ Est2014 |
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2578 |
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