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Marc Bolaños, R. Mestre, Estefania Talavera, Xavier Giro, & Petia Radeva. (2015). Visual Summary of Egocentric Photostreams by Representative Keyframes. In IEEE International Conference on Multimedia and Expo ICMEW2015 (pp. 1–6).
Abstract: Building a visual summary from an egocentric photostream captured by a lifelogging wearable camera is of high interest for different applications (e.g. memory reinforcement). In this paper, we propose a new summarization method based on keyframes selection that uses visual features extracted bymeans of a convolutional neural network. Our method applies an unsupervised clustering for dividing the photostreams into events, and finally extracts the most relevant keyframe for each event. We assess the results by applying a blind-taste test on a group of 20 people who assessed the quality of the
summaries.
Keywords: egocentric; lifelogging; summarization; keyframes
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Fernando Vilariño. (2006). A Machine Learning Approach for Intestinal Motility Assessment with Capsule Endoscopy (Petia Radeva, Ed.). Ph.D. thesis, , .
Abstract: Intestinal motility assessment with video capsule endoscopy arises as a novel and challenging clinical fieldwork. This technique is based on the analysis of the patterns of intestinal contractions obtained by labelling all the motility events present in a video provided by a capsule with a wireless micro-camera, which is ingested by the patient. However, the visual analysis of these video sequences presents several im- portant drawbacks, mainly related to both the large amount of time needed for the visualization process, and the low prevalence of intestinal contractions in video.
In this work we propose a machine learning system to automatically detect the intestinal contractions in video capsule endoscopy, driving a very useful but not fea- sible clinical routine into a feasible clinical procedure. Our proposal is divided into two different parts: The first part tackles the problem of the automatic detection of phasic contractions in capsule endoscopy videos. Phasic contractions are dynamic events spanning about 4-5 seconds, which show visual patterns with a high variability. Our proposal is based on a sequential design which involves the analysis of textural, color and blob features with powerful classifiers such as SVM. This approach appears to cope with two basic aims: the reduction of the imbalance rate of the data set, and the modular construction of the system, which adds the capability of including domain knowledge as new stages in the cascade. The second part of the current work tackles the problem of the automatic detection of tonic contractions. Tonic contrac- tions manifest in capsule endoscopy as a sustained pattern of the folds and wrinkles of the intestine, which may be prolonged for an undetermined span of time. Our proposal is based on the analysis of the wrinkle patterns, presenting a comparative study of diverse features and classification methods, and providing a set of appro- priate descriptors for their characterization. We provide a detailed analysis of the performance achieved by our system both in a qualitative and a quantitative way.
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Josep Llados, J. Lopez-Krahe, & Enric Marti. (1999). A Hough-based method for hatched pattern detection in maps and diagrams..
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Felipe Lumbreras, Ramon Baldrich, Maria Vanrell, Joan Serrat, & Juan J. Villanueva. (1999). Multiresolution colour texture representations for tile classification.
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Daniel Ponsa, A.F. Sole, Antonio Lopez, Cristina Cañero, Petia Radeva, & Jordi Vitria. (1999). Regularized EM.
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David Guillamet, & Jordi Vitria. (1999). Using Eigenspace analysis of color distributions for object recognition.
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A. Pujol, Felipe Lumbreras, X. Varona, & Juan J. Villanueva. (1999). Template matching through invariant eigenspace projection..
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Josep Llados, Felipe Lumbreras, & X. Varona. (1999). A multidocument platform for automatic reading of identity cards..
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A. Martinez, & Jordi Vitria. (1998). Learning mixture models with the EM algorithm and genetic algorithms.
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A.F. Sole, Antonio Lopez, Cristina Cañero, Petia Radeva, & J. Saludes. (1999). Crease enhancement diffusion.
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X. Varona, A. Pujol, & Juan J. Villanueva. (1999). Visual tracking in application domains..
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Antonio Lopez, David Lloret, & Joan Serrat. (1998). Creaseness measures for CT and MR image registration..
Abstract: Creases are a type of ridge/valley structures that can be characterized by local conditions. Therefore, creaseness refers to local ridgeness and valleyness. The curvature K of the level curves and the mean curvature kM of the level surfaces are good measures of creaseness for 2-d and 3-d images, respectively. However, the way they are computed gives rise to discontinuities, reducing their usefulness in many applications. We propose a new creaseness measure, based on these curvatures, that avoids the discontinuities. We demonstrate its usefulness in the registration of CT and MR brain volumes, from the same patient, by searching the maximum in the correlation of their creaseness responses (ridgeness from the CT and valleyness from the MR). Due to the high dimensionality of the space of transforms, the search is performed by a hierarchical approach combined with an optimization method at each level of the hierarchy
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Antonio Lopez, Felipe Lumbreras, & Joan Serrat. (1998). Creaseness form level set extrinsec curvature..
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Xavier Roca, Jordi Vitria, Maria Vanrell, & Juan J. Villanueva. (1999). Visual behaviours for binocular navigation with autonomous systems..
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Antonio Lopez, Ricardo Toledo, Joan Serrat, & Juan J. Villanueva. (1999). Extraction of vessel centerlines from 2D coronary angiographies.
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