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Ernest Valveny, & Enric Marti. (1997)." Dimensions analysis in hand-drawn architectural drawings" In VII National Simposium of Pattern Recognition and image Analysis, SNRFAI´97 (pp. 90–91). CVC-UAB.
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Jorge Bernal, Debora Gil, Carles Sanchez, & F. Javier Sanchez. (2014). "Discarding Non Informative Regions for Efficient Colonoscopy Image Analysis " In 1st MICCAI Workshop on Computer-Assisted and Robotic Endoscopy (Vol. 8899, pp. 1–10). Springer International Publishing.
Abstract: In this paper we present a novel polyp region segmentation method for colonoscopy videos. Our method uses valley information associated to polyp boundaries in order to provide an initial segmentation. This first segmentation is refined to eliminate boundary discontinuities caused by image artifacts or other elements of the scene. Experimental results over a publicly annotated database show that our method outperforms both general and specific segmentation methods by providing more accurate regions rich in polyp content. We also prove how image preprocessing is needed to improve final polyp region segmentation.
Keywords: Image Segmentation; Polyps, Colonoscopy; Valley Information; Energy Maps
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Oriol Rodriguez-Leon, Josefina Mauri, Eduard Fernandez-Nofrerias, M.Gomez, Antonio Tovar, L.Cano, et al. (2002)." Ecografia Intracoronària: Segmentació Automàtica de area de la llum" In XXXVIII Congreso Nacional de la Sociedad Española de Cardiología..
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Joan Serrat, & Enric Marti. (1991)." Elastic matching using interpolation splines" In IV Spanish Symposium of Pattern Recognition and image Analysis.
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Patricia Marquez, Debora Gil, & Aura Hernandez-Sabate. (2012). "Error Analysis for Lucas-Kanade Based Schemes " In 9th International Conference on Image Analysis and Recognition (Vol. 7324, pp. 184–191). Lecture Notes in Computer Science. Springer-Verlag Berlin Heidelberg.
Abstract: Optical flow is a valuable tool for motion analysis in medical imaging sequences. A reliable application requires determining the accuracy of the computed optical flow. This is a main challenge given the absence of ground truth in medical sequences. This paper presents an error analysis of Lucas-Kanade schemes in terms of intrinsic design errors and numerical stability of the algorithm. Our analysis provides a confidence measure that is naturally correlated to the accuracy of the flow field. Our experiments show the higher predictive value of our confidence measure compared to existing measures.
Keywords: Optical flow, Confidence measure, Lucas-Kanade, Cardiac Magnetic Resonance
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Patricia Marquez, Debora Gil, & Aura Hernandez-Sabate. (2013). "Evaluation of the Capabilities of Confidence Measures for Assessing Optical Flow Quality " In ICCV Workshop on Computer Vision in Vehicle Technology: From Earth to Mars (pp. 624–631).
Abstract: 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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Francesco Brughi, Debora Gil, Llorenç Badiella, Eva Jove Casabella, & Oriol Ramos Terrades. (2014). "Exploring the impact of inter-query variability on the performance of retrieval systems " In 11th International Conference on Image Analysis and Recognition (Vol. 8814, 413–420). Springer International Publishing.
Abstract: 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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Aura Hernandez-Sabate, Lluis Albarracin, Daniel Calvo, & Nuria Gorgorio. (2016). "EyeMath: Identifying Mathematics Problem Solving Processes in a RTS Video Game " In 5th International Conference Games and Learning Alliance (Vol. 10056, pp. 50–59).
Abstract: Photorealistic virtual environments are crucial for developing and testing automated driving systems in a safe way during trials. As commercially available simulators are expensive and bulky, this paper presents a low-cost, extendable, and easy-to-use (LEE) virtual environment with the aim to highlight its utility for level 3 driving automation. In particular, an experiment is performed using the presented simulator to explore the influence of different variables regarding control transfer of the car after the system was driving autonomously in a highway scenario. The results show that the speed of the car at the time when the system needs to transfer the control to the human driver is critical.
Keywords: Simulation environment; Automated Driving; Driver-Vehicle interaction
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Petia Radeva, & Enric Marti. (1995). Facial Features Segmentation by Model-Based Snakes In International Conference on Computing Analysis and Image Processing. Bellaterra (Barcelona), Spain.
Abstract: Deformable models have recently been accepted as a standard technique to segment different features in facial images. Despite they give a good approximation of the salient features in a facial image, the resulting shapes of the segmentation process seem somewhat artificial with respect to the natural feature shapes. In this paper we show that active contour models (in particular, rubber snakes) give more close and natural representation of the detected feature shape. Besides, using snakes for facial segmentation frees us from the problem of determination of the numerous weigths of deformable models. Another advantage of rubber snakes is their reduced computational cost. Our experiments using rubber snakes for segmentation of facial snapshots have shown a significant improvement compared to deformable models.
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Patricia Marquez, H. Kause, A. Fuster, Aura Hernandez-Sabate, L. Florack, Debora Gil, et al. (2014). "Factors Affecting Optical Flow Performance in Tagging Magnetic Resonance Imaging " In 17th International Conference on Medical Image Computing and Computer Assisted Intervention (Vol. 8896, pp. 231–238). Springer International Publishing.
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 di erent 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 di erent OF methods, including HARP.
Keywords: Optical flow; Performance Evaluation; Synthetic Database; ANOVA; Tagging Magnetic Resonance Imaging
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