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Author |
Marçal Rusiñol; Josep Llados |
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Title |
Logo Spotting by a Bag-of-words Approach for Document Categorization |
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Conference Article |
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Year |
2009 |
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10th International Conference on Document Analysis and Recognition |
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111–115 |
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In this paper we present a method for document categorization which processes incoming document images such as invoices or receipts. The categorization of these document images is done in terms of the presence of a certain graphical logo detected without segmentation. The graphical logos are described by a set of local features and the categorization of the documents is performed by the use of a bag-of-words model. Spatial coherence rules are added to reinforce the correct category hypothesis, aiming also to spot the logo inside the document image. Experiments which demonstrate the effectiveness of this system on a large set of real data are presented. |
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Barcelona; Spain |
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1520-5363 |
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978-1-4244-4500-4 |
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ICDAR |
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DAG |
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DAG @ dag @ RuL2009b |
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1179 |
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Author |
Maya Dimitrova; Ch. Roumenin; Siya Lozanova; David Rotger; Petia Radeva |
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Title |
An Interface System Based on Multimodal Principle for Cardiological Diagnosis Assistance |
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Conference Article |
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2007 |
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International Conference On Computer Systems And Technologies |
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IIIB.4 |
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1–6 |
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Bulgaria |
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CompSysTech’07 |
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MILAB |
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BCNPCL @ bcnpcl @ DRL2007 |
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833 |
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Author |
Veronica Romero; Emilio Granell; Alicia Fornes; Enrique Vidal; Joan Andreu Sanchez |
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Title |
Information Extraction in Handwritten Marriage Licenses Books |
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Conference Article |
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Year |
2019 |
Publication |
5th International Workshop on Historical Document Imaging and Processing |
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66-71 |
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Handwritten marriage licenses books are characterized by a simple structure of the text in the records with an evolutionary vocabulary, mainly composed of proper names that change along the time. This distinct vocabulary makes automatic transcription and semantic information extraction difficult tasks. Previous works have shown that the use of category-based language models and a Grammatical Inference technique known as MGGI can improve the accuracy of these
tasks. However, the application of the MGGI algorithm requires an a priori knowledge to label the words of the training strings, that is not always easy to obtain. In this paper we study how to automatically obtain the information required by the MGGI algorithm using a technique based on Confusion Networks. Using the resulting language model, full handwritten text recognition and information extraction experiments have been carried out with results supporting the proposed approach. |
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Sydney; Australia; September 2019 |
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HIP |
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DAG; 600.140; 600.121 |
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Admin @ si @ RGF2019 |
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3352 |
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Author |
Antonio Lopez |
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Title |
Ridge/Valley-like structures: Creases, separatrices and drainage patterns |
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Miscellaneous |
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1997 |
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Computer vision on–line |
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CVC |
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ADAS |
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ADAS @ adas @ Lop1997 |
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488 |
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Author |
Xavier Otazu; Olivier Penacchio; Xim Cerda-Company |
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Title |
Brightness and colour induction through contextual influences in V1 |
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Conference Article |
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2015 |
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Scottish Vision Group 2015 SGV2015 |
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12 |
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9 |
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1208-2012 |
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Carnoustie; Scotland; March 2015 |
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SGV |
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NEUROBIT;CIC |
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no |
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Admin @ si @ OPC2015a |
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2632 |
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Author |
Antoni Gurgui; Debora Gil; Enric Marti |
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Title |
Laplacian Unitary Domain for Texture Morphing |
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Conference Article |
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Year |
2015 |
Publication |
Proceedings of the 10th International Conference on Computer Vision Theory and Applications VISIGRAPP2015 |
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1 |
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693-699 |
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Keywords |
Facial; metamorphosis;LaplacianMorphing |
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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. |
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Munich; Germany; February 2015 |
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SciTePress |
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978-989-758-089-5 |
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VISAPP |
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Notes |
IAM; 600.075 |
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no |
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Call Number |
Admin @ si @ GGM2015 |
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2614 |
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Author |
Ishaan Gulrajani; Kundan Kumar; Faruk Ahmed; Adrien Ali Taiga; Francesco Visin; David Vazquez; Aaron Courville |
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Title |
PixelVAE: A Latent Variable Model for Natural Images |
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Conference Article |
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Year |
2017 |
Publication |
5th International Conference on Learning Representations |
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Deep Learning; Unsupervised Learning |
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Natural image modeling is a landmark challenge of unsupervised learning. Variational Autoencoders (VAEs) learn a useful latent representation and generate samples that preserve global structure but tend to suffer from image blurriness. PixelCNNs model sharp contours and details very well, but lack an explicit latent representation and have difficulty modeling large-scale structure in a computationally efficient way. In this paper, we present PixelVAE, a VAE model with an autoregressive decoder based on PixelCNN. The resulting architecture achieves state-of-the-art log-likelihood on binarized MNIST. We extend PixelVAE to a hierarchy of multiple latent variables at different scales; this hierarchical model achieves competitive likelihood on 64x64 ImageNet and generates high-quality samples on LSUN bedrooms. |
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Toulon; France; April 2017 |
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ICLR |
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Notes |
ADAS; 600.085; 600.076; 601.281; 600.118 |
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no |
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ADAS @ adas @ GKA2017 |
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2815 |
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Author |
Eric Amiel |
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Title |
Visualisation de vaisseaux sanguins |
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Report |
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2005 |
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Rapport de Stage |
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Université Paul Sabatier Toulouse III |
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Bachelor's thesis |
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Publisher |
Université Paul Sabatier Toulouse III |
Place of Publication |
Toulouse |
Editor |
Enric Marti |
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Language |
French |
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French |
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IUP Systèmes Intelligents |
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IAM |
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no |
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IAM @ iam @ Ami2005 |
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1690 |
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Author |
Alejandro Cartas; Mariella Dimiccoli; Petia Radeva |
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Title |
Batch-based activity recognition from egocentric photo-streams |
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Conference Article |
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Year |
2017 |
Publication |
1st International workshop on Egocentric Perception, Interaction and Computing |
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Activity recognition from long unstructured egocentric photo-streams has several applications in assistive technology such as health monitoring and frailty detection, just to name a few. However, one of its main technical challenges is to deal with the low frame rate of wearable photo-cameras, which causes abrupt appearance changes between consecutive frames. In consequence, important discriminatory low-level features from motion such as optical flow cannot be estimated. In this paper, we present a batch-driven approach for training a deep learning architecture that strongly rely on Long short-term units to tackle this problem. We propose two different implementations of the same approach that process a photo-stream sequence using batches of fixed size with the goal of capturing the temporal evolution of high-level features. The main difference between these implementations is that one explicitly models consecutive batches by overlapping them. Experimental results over a public dataset acquired by three users demonstrate the validity of the proposed architectures to exploit the temporal evolution of convolutional features over time without relying on event boundaries. |
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Venice; Italy; October 2017; |
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ICCV - EPIC |
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MILAB; no menciona |
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no |
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Call Number |
Admin @ si @ CDR2017 |
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3023 |
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Author |
Chen Zhang; Maria del Mar Vila Muñoz; Petia Radeva; Roberto Elosua; Maria Grau; Angels Betriu; Elvira Fernandez-Giraldez; Laura Igual |
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Title |
Carotid Artery Segmentation in Ultrasound Images |
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Conference Article |
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Year |
2015 |
Publication |
Computing and Visualization for Intravascular Imaging and Computer Assisted Stenting (CVII-STENT2015), Joint MICCAI Workshops |
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Munich; Germany; October 2015 |
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CVII-STENT |
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MILAB |
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no |
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Call Number |
Admin @ si @ ZVR2015 |
Serial |
2675 |
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Author |
Jorge Bernal; F. Javier Sanchez; Fernando Vilariño |
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Title |
Depth of Valleys Accumulation Algorithm for Object Detection |
Type |
Conference Article |
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Year |
2011 |
Publication |
14th Congrès Català en Intel·ligencia Artificial |
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Volume |
1 |
Issue |
1 |
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71-80 |
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Object Recognition, Object Region Identification, Image Analysis, Image Processing |
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Abstract |
This work aims at detecting in which regions the objects in the image are by using information about the intensity of valleys, which appear to surround ob- jects in images where the source of light is in the line of direction than the camera. We present our depth of valleys accumulation method, which consists of two stages: first, the definition of the depth of valleys image which combines the output of a ridges and valleys detector with the morphological gradient to measure how deep is a point inside a valley and second, an algorithm that denotes points of the image as interior to objects those which are inside complete or incomplete boundaries in the depth of valleys image. To evaluate the performance of our method we have tested it on several application domains. Our results on object region identification are promising, specially in the field of polyp detection in colonoscopy videos, and we also show its applicability in different areas. |
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Lleida |
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978-1-60750-841-0 |
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800 |
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CCIA |
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MV;SIAI |
Approved |
no |
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Call Number |
IAM @ iam @ BSV2011b |
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1699 |
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Author |
David Roche; Debora Gil; Jesus Giraldo |
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Title |
An inference model for analyzing termination conditions of Evolutionary Algorithms |
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Conference Article |
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Year |
2011 |
Publication |
14th Congrès Català en Intel·ligencia Artificial |
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216-225 |
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Evolutionary Computation Convergence, Termination Conditions, Statistical Inference |
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In real-world problems, it is mandatory to design a termination condition for Evolutionary Algorithms (EAs) ensuring stabilization close to the unknown optimum. Distribution-based quantities are good candidates as far as suitable parameters are used. A main limitation for application to real-world problems is that such parameters strongly depend on the topology of the objective function, as well as, the EA paradigm used.
We claim that the termination problem would be fully solved if we had a model measuring to what extent a distribution-based quantity asymptotically behaves like the solution accuracy. We present a regression-prediction model that relates any two given quantities and reports if they can be statistically swapped as termination conditions. Our framework is applied to two issues. First, exploring if the parameters involved in the computation of distribution-based quantities influence their asymptotic behavior. Second, to what extent existing distribution-based quantities can be asymptotically exchanged for the accuracy of the EA solution. |
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Address |
Lleida, Catalonia (Spain) |
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Associació Catalana Intel·ligència Artificial |
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978-1-60750-841-0 |
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CCIA |
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IAM |
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IAM @ iam @ RGG2011a |
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1677 |
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Author |
Sergio Alloza; Flavio Escribano; Sergi Delgado; Ciprian Corneanu; Sergio Escalera |
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Title |
XBadges. Identifying and training soft skills with commercial video games Improving persistence, risk taking & spatial reasoning with commercial video games and facial and emotional recognition system |
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Conference Article |
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Year |
2017 |
Publication |
4th Congreso de la Sociedad Española para las Ciencias del Videojuego |
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Volume |
1957 |
Issue |
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Pages |
13-28 |
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Keywords |
Video Games; Soft Skills; Training; Skilling Development; Emotions; Cognitive Abilities; Flappy Bird; Pacman; Tetris |
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Abstract |
XBadges is a research project based on the hypothesis that commercial video games (nonserious games) can train soft skills. We measure persistence, patial reasoning and risk taking before and after subjects paticipate in controlled game playing sessions.
In addition, we have developed an automatic facial expression recognition system capable of inferring their emotions while playing, allowing us to study the role of emotions in soft skills acquisition. We have used Flappy Bird, Pacman and Tetris for assessing changes in persistence, risk taking and spatial reasoning respectively.
Results show how playing Tetris significantly improves spatial reasoning and how playing Pacman significantly improves prudence in certain areas of behavior. As for emotions, they reveal that being concentrated helps to improve performance and skills acquisition. Frustration is also shown as a key element. With the results obtained we are able to glimpse multiple applications in areas which need soft skills development. |
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Barcelona; June 2017 |
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COSECIVI; CEUR-WS |
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Notes |
HUPBA; no menciona |
Approved |
no |
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Call Number |
Admin @ si @ AED2017 |
Serial |
3065 |
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Permanent link to this record |
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Author |
Debora Gil; Petia Radeva |
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Title |
Curvature Vector Flow to Assure Convergent Deformable Models for Shape Modelling |
Type |
Book Chapter |
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Year |
2003 |
Publication |
Energy Minimization Methods In Computer Vision And Pattern Recognition |
Abbreviated Journal |
LNCS |
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Volume |
2683 |
Issue |
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Pages |
357-372 |
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Initial condition; Convex shape; Non convex analysis; Increase; Segmentation; Gradient; Standard; Standards; Concave shape; Flow models; Tracking; Edge detection; Curvature |
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Abstract |
Poor convergence to concave shapes is a main limitation of snakes as a standard segmentation and shape modelling technique. The gradient of the external energy of the snake represents a force that pushes the snake into concave regions, as its internal energy increases when new inexion points are created. In spite of the improvement of the external energy by the gradient vector ow technique, highly non convex shapes can not be obtained, yet. In the present paper, we develop a new external energy based on the geometry of the curve to be modelled. By tracking back the deformation of a curve that evolves by minimum curvature ow, we construct a distance map that encapsulates the natural way of adapting to non convex shapes. The gradient of this map, which we call curvature vector ow (CVF), is capable of attracting a snake towards any contour, whatever its geometry. Our experiments show that, any initial snake condition converges to the curve to be modelled in optimal time. |
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Springer, Berlin |
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Lisbon, PORTUGAL |
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Springer, B. |
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Lecture Notes in Computer Science |
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LNCS |
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ISSN |
0302-9743 |
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3-540-40498-8 |
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IAM @ iam @ GIR2003b |
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1535 |
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Author |
Debora Gil; Petia Radeva; Jordi Saludes; Josefina Mauri |
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Title |
Automatic Segmentation of Artery Wall in Coronary IVUS Images: A Probabilistic Approach |
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Conference Article |
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2000 |
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International Conference on Pattern Recognition |
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4 |
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352-355 |
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Abstract |
Intravascular ultrasound images represent a unique tool to analyze the morphology of arteries and vessels (plaques, restenosis, etc). The poor quality of these images makes unsupervised segmentation based on traditional segmentation algorithms (such as edge or ridge/valley detection) fail to achieve the expected results. In this paper we present a probabilistic flexible template to separate different regions in the image. In particular, we use elliptic templates to model and detect the shape of the vessel inner wall in IVUS images. We present the results of successful segmentation obtained from patients undergoing stent treatment. A physician team has validated these results. |
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IAM;MILAB |
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IAM @ iam @ GRS2000a |
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1537 |
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