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Carles Sanchez, Debora Gil, R. Tazi, Jorge Bernal, Y. Ruiz, L. Planas, et al. (2015). Quasi-real time digital assessment of Central Airway Obstruction. In 3rd European congress for bronchology and interventional pulmonology ECBIP2015.
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Carles Sanchez, Jorge Bernal, F. Javier Sanchez, Marta Diez-Ferrer, Antoni Rosell, & Debora Gil. (2015). Towards On-line Quantification of Tracheal Stenosis from Videobronchoscopy. In 6th International Conference on Information Processing in Computer-Assisted Interventions IPCAI2015 (Vol. 10, pp. 935–945).
Abstract: PURPOSE:
Lack of objective measurement of tracheal obstruction degree has a negative impact on the chosen treatment prone to lead to unnecessary repeated explorations and other scanners. Accurate computation of tracheal stenosis in videobronchoscopy would constitute a breakthrough for this noninvasive technique and a reduction in operation cost for the public health service.
METHODS:
Stenosis calculation is based on the comparison of the region delimited by the lumen in an obstructed frame and the region delimited by the first visible ring in a healthy frame. We propose a parametric strategy for the extraction of lumen and tracheal ring regions based on models of their geometry and appearance that guide a deformable model. To ensure a systematic applicability, we present a statistical framework to choose optimal parametric values and a strategy to choose the frames that minimize the impact of scope optical distortion.
RESULTS:
Our method has been tested in 40 cases covering different stenosed tracheas. Experiments report a non- clinically relevant [Formula: see text] of discrepancy in the calculated stenotic area and a computational time allowing online implementation in the operating room.
CONCLUSIONS:
Our methodology allows reliable measurements of airway narrowing in the operating room. To fully assess its clinical impact, a prospective clinical trial should be done.
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Antoni Gurgui, Debora Gil, & Enric Marti. (2015). Laplacian Unitary Domain for Texture Morphing. In Proceedings of the 10th International Conference on Computer Vision Theory and Applications VISIGRAPP2015 (Vol. 1, pp. 693–699). SciTePress.
Abstract: Deformation of expressive textures is the gateway to realistic computer synthesis of expressions. By their good mathematical properties and flexible formulation on irregular meshes, most texture mappings rely on solutions to the Laplacian in the cartesian space. In the context of facial expression morphing, this approximation can be seen from the opposite point of view by neglecting the metric. In this paper, we use the properties of the Laplacian in manifolds to present a novel approach to warping expressive facial images in order to generate a morphing between them.
Keywords: Facial; metamorphosis;LaplacianMorphing
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Sergio Vera, Miguel Angel Gonzalez Ballester, & Debora Gil. (2015). A Novel Cochlear Reference Frame Based On The Laplace Equation. In 29th international Congress and Exhibition on Computer Assisted Radiology and Surgery (Vol. 10, pp. 1–312).
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Hanne Kause, Patricia Marquez, Andrea Fuster, Aura Hernandez-Sabate, Luc Florack, Debora Gil, et al. (2015). Quality Assessment of Optical Flow in Tagging MRI. In 5th Dutch Bio-Medical Engineering Conference BME2015.
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Olivier Lefebvre, Pau Riba, Charles Fournier, Alicia Fornes, Josep Llados, Rejean Plamondon, et al. (2015). Monitoring neuromotricity on-line: a cloud computing approach. In 17th Conference of the International Graphonomics Society IGS2015.
Abstract: The goal of our experiment is to develop a useful and accessible tool that can be used to evaluate a patient's health by analyzing handwritten strokes. We use a cloud computing approach to analyze stroke data sampled on a commercial tablet working on the Android platform and a distant server to perform complex calculations using the Delta and Sigma lognormal algorithms. A Google Drive account is used to store the data and to ease the development of the project. The communication between the tablet, the cloud and the server is encrypted to ensure biomedical information confidentiality. Highly parameterized biomedical tests are implemented on the tablet as well as a free drawing test to evaluate the validity of the data acquired by the first test compared to the second one. A blurred shape model descriptor pattern recognition algorithm is used to classify the data obtained by the free drawing test. The functions presented in this paper are still currently under development and other improvements are needed before launching the application in the public domain.
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Pau Riba, Josep Llados, Alicia Fornes, & Anjan Dutta. (2015). Large-scale Graph Indexing using Binary Embeddings of Node Contexts. In C.-L.Liu, B.Luo, W.G.Kropatsch, & J.Cheng (Eds.), 10th IAPR-TC15 Workshop on Graph-based Representations in Pattern Recognition (Vol. 9069, pp. 208–217). LNCS. Springer International Publishing.
Abstract: Graph-based representations are experiencing a growing usage in visual recognition and retrieval due to their representational power in front of classical appearance-based representations in terms of feature vectors. Retrieving a query graph from a large dataset of graphs has the drawback of the high computational complexity required to compare the query and the target graphs. The most important property for a large-scale retrieval is the search time complexity to be sub-linear in the number of database examples. In this paper we propose a fast indexation formalism for graph retrieval. A binary embedding is defined as hashing keys for graph nodes. Given a database of labeled graphs, graph nodes are complemented with vectors of attributes representing their local context. Hence, each attribute counts the length of a walk of order k originated in a vertex with label l. Each attribute vector is converted to a binary code applying a binary-valued hash function. Therefore, graph retrieval is formulated in terms of finding target graphs in the database whose nodes have a small Hamming distance from the query nodes, easily computed with bitwise logical operators. As an application example, we validate the performance of the proposed methods in a handwritten word spotting scenario in images of historical documents.
Keywords: Graph matching; Graph indexing; Application in document analysis; Word spotting; Binary embedding
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Joan Arnedo-Moreno, D. Bañeres, Xavier Baro, S. Caballe, S. Guerrero, L. Porta, et al. (2014). Va-ID: A trust-based virtual assessment system. In 6th International Conference on Intelligent Networking and Collaborative Systems (pp. 328–335).
Abstract: Even though online education is a very important pillar of lifelong education, institutions are still reluctant to wager for a fully online educational model. At the end, they keep relying on on-site assessment systems, mainly because fully virtual alternatives do not have the deserved social recognition or credibility. Thus, the design of virtual assessment systems that are able to provide effective proof of student authenticity and authorship and the integrity of the activities in a scalable and cost efficient manner would be very helpful. This paper presents ValID, a virtual assessment approach based on a continuous trust level evaluation between students and the institution. The current trust level serves as the main mechanism to dynamically decide which kind of controls a given student should be subjected to, across different courses in a degree. The main goal is providing a fair trade-off between security, scalability and cost, while maintaining the perceived quality of the educational model.
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B. Zhou, Agata Lapedriza, J. Xiao, A. Torralba, & A. Oliva. (2014). Learning Deep Features for Scene Recognition using Places Database. In 28th Annual Conference on Neural Information Processing Systems (pp. 487–495).
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Agata Lapedriza, David Masip, & D.Sanchez. (2014). Emotions Classification using Facial Action Units Recognition. In 17th International Conference of the Catalan Association for Artificial Intelligence (Vol. 269, pp. 55–64).
Abstract: In this work we build a system for automatic emotion classification from image sequences. We analyze subtle changes in facial expressions by detecting a subset of 12 representative facial action units (AUs). Then, we classify emotions based on the output of these AUs classifiers, i.e. the presence/absence of AUs. We base the AUs classification upon a set of spatio-temporal geometric and appearance features for facial representation, fusing them within the emotion classifier. A decision tree is trained for emotion classifying, making the resulting model easy to interpret by capturing the combination of AUs activation that lead to a particular emotion. For Cohn-Kanade database, the proposed system classifies 7 emotions with a mean accuracy of near 90%, attaining a similar recognition accuracy in comparison with non-interpretable models that are not based in AUs detection.
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Youssef El Rhabi, Simon Loic, & Brun Luc. (2015). Estimation de la pose d’une caméra à partir d’un flux vidéo en s’approchant du temps réel. In 15ème édition d'ORASIS, journées francophones des jeunes chercheurs en vision par ordinateur ORASIS2015.
Abstract: Finding a way to estimate quickly and robustly the pose of an image is essential in augmented reality. Here we will discuss the approach we chose in order to get closer to real time by using SIFT points [4]. We propose a method based on filtering both SIFT points and images on which to focus on. Hence we will focus on relevant data.
Keywords: Augmented Reality; SFM; SLAM; real time pose computation; 2D/3D registration
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Bogdan Raducanu, Alireza Bosaghzadeh, & Fadi Dornaika. (2015). Multi-observation Face Recognition in Videos based on Label Propagation. In 6th Workshop on Analysis and Modeling of Faces and Gestures AMFG2015 (pp. 10–17).
Abstract: In order to deal with the huge amount of content generated by social media, especially for indexing and retrieval purposes, the focus shifted from single object recognition to multi-observation object recognition. Of particular interest is the problem of face recognition (used as primary cue for persons’ identity assessment), since it is highly required by popular social media search engines like Facebook and Youtube. Recently, several approaches for graph-based label propagation were proposed. However, the associated graphs were constructed in an ad-hoc manner (e.g., using the KNN graph) that cannot cope properly with the rapid and frequent changes in data appearance, a phenomenon intrinsically related with video sequences. In this paper, we
propose a novel approach for efficient and adaptive graph construction, based on a two-phase scheme: (i) the first phase is used to adaptively find the neighbors of a sample and also to find the adequate weights for the minimization function of the second phase; (ii) in the second phase, the
selected neighbors along with their corresponding weights are used to locally and collaboratively estimate the sparse affinity matrix weights. Experimental results performed on Honda Video Database (HVDB) and a subset of video
sequences extracted from the popular TV-series ’Friends’ show a distinct advantage of the proposed method over the existing standard graph construction methods.
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M. Cruz, Cristhian A. Aguilera-Carrasco, Boris X. Vintimilla, Ricardo Toledo, & Angel Sappa. (2015). Cross-spectral image registration and fusion: an evaluation study. In 2nd International Conference on Machine Vision and Machine Learning.
Abstract: This paper presents a preliminary study on the registration and fusion of cross-spectral imaging. The objective is to evaluate the validity of widely used computer vision approaches when they are applied at different
spectral bands. In particular, we are interested in merging images from the infrared (both long wave infrared: LWIR and near infrared: NIR) and visible spectrum (VS). Experimental results with different data sets are presented.
Keywords: multispectral imaging; image registration; data fusion; infrared and visible spectra
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Cristhian A. Aguilera-Carrasco, Angel Sappa, & Ricardo Toledo. (2015). LGHD: a Feature Descriptor for Matching Across Non-Linear Intensity Variations. In 22th IEEE International Conference on Image Processing (pp. 178–181).
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Xavier Otazu, Olivier Penacchio, & Xim Cerda-Company. (2015). Brightness and colour induction through contextual influences in V1. In Scottish Vision Group 2015 SGV2015 (Vol. 12, pp. 1208–2012).
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