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Author |
Victor Ponce; Hugo Jair Escalante; Sergio Escalera; Xavier Baro |
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Title |
Gesture and Action Recognition by Evolved Dynamic Subgestures |
Type |
Conference Article |
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Year |
2015 |
Publication |
26th British Machine Vision Conference |
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129.1-129.13 |
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This paper introduces a framework for gesture and action recognition based on the evolution of temporal gesture primitives, or subgestures. Our work is inspired on the principle of producing genetic variations within a population of gesture subsequences, with the goal of obtaining a set of gesture units that enhance the generalization capability of standard gesture recognition approaches. In our context, gesture primitives are evolved over time using dynamic programming and generative models in order to recognize complex actions. In few generations, the proposed subgesture-based representation
of actions and gestures outperforms the state of the art results on the MSRDaily3D and MSRAction3D datasets. |
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Swansea; uk; September 2015 |
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BMVC |
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HuPBA;MV |
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no |
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Admin @ si @ PEE2015 |
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2657 |
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Author |
Naila Murray; Luca Marchesotti; Florent Perronnin |
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Title |
Learning to Rank Images using Semantic and Aesthetic Labels |
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Conference Article |
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Year |
2012 |
Publication |
23rd British Machine Vision Conference |
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110.1-110.10 |
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Most works on image retrieval from text queries have addressed the problem of retrieving semantically relevant images. However, the ability to assess the aesthetic quality of an image is an increasingly important differentiating factor for search engines. In this work, given a semantic query, we are interested in retrieving images which are semantically relevant and score highly in terms of aesthetics/visual quality. We use large-margin classifiers and rankers to learn statistical models capable of ordering images based on the aesthetic and semantic information. In particular, we compare two families of approaches: while the first one attempts to learn a single ranker which takes into account both semantic and aesthetic information, the second one learns separate semantic and aesthetic models. We carry out a quantitative and qualitative evaluation on a recently-published large-scale dataset and we show that the second family of techniques significantly outperforms the first one. |
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Guildford, London |
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1-901725-46-4 |
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BMVC |
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CIC |
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no |
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Admin @ si @ MMP2012b |
Serial |
2027 |
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Author |
Jorge Bernal; F. Javier Sanchez; Fernando Vilariño |
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Title |
Current Challenges on Polyp Detection in Colonoscopy Videos: From Region Segmentation to Region Classification. a Pattern Recognition-based Approach.ased Approach |
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Conference Article |
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Year |
2011 |
Publication |
2nd International Workshop on Medical Image Analysis and Descriptionfor Diagnosis Systems |
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62-71 |
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Keywords |
Medical Imaging, Colonoscopy, Pattern Recognition, Segmentation, Polyp Detection, Region Description, Machine Learning, Real-time. |
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Abstract |
In this paper we present our approach on real-time polyp detection in colonoscopy videos. Our method consists of three stages: Image Segmentation, Region Description and Image Classification. Taking into account the constraints of our project, we introduce our segmentation system that is based on the model of appearance of the polyp that we have defined after observing real videos from colonoscopy processes. The output of this stage will ideally be a low number of regions of which one of them should cover the whole polyp region (if there is one in the image). This regions will be described in terms of features and, as a result of a machine learning schema, classified based on the values that they have for the several features that we will use on their description. Although we are still on the early stages of the project, we present some preliminary segmentation results that indicates that we are going in a good direction. |
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Rome, Italy |
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SciTePress |
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Djemal, Khalifa |
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800 |
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MIAD |
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MV;SIAI |
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no |
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Call Number |
IAM @ iam @ BSV2011a |
Serial |
1695 |
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Author |
Maurizio Mencuccini; Jordi Martinez-Vilalta; Josep Piñol; Lasse Loepfe; Mireia Burnat ; Xavier Alvarez; Juan Camacho; Debora Gil |
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Title |
A quantitative and statistically robust method for the determination of xylem conduit spatial distribution |
Type |
Journal Article |
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Year |
2010 |
Publication |
American Journal of Botany |
Abbreviated Journal |
AJB |
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Volume |
97 |
Issue |
8 |
Pages |
1247-1259 |
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Keywords |
Geyer; hydraulic conductivity; point pattern analysis; Ripley; Spatstat; vessel clusters; xylem anatomy; xylem network |
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Abstract |
Premise of the study: Because of their limited length, xylem conduits need to connect to each other to maintain water transport from roots to leaves. Conduit spatial distribution in a cross section plays an important role in aiding this connectivity. While indices of conduit spatial distribution already exist, they are not well defined statistically. * Methods: We used point pattern analysis to derive new spatial indices. One hundred and five cross-sectional images from different species were transformed into binary images. The resulting point patterns, based on the locations of the conduit centers-of-area, were analyzed to determine whether they departed from randomness. Conduit distribution was then modeled using a spatially explicit stochastic model. * Key results: The presence of conduit randomness, uniformity, or aggregation depended on the spatial scale of the analysis. The large majority of the images showed patterns significantly different from randomness at least at one spatial scale. A strong phylogenetic signal was detected in the spatial variables. * Conclusions: Conduit spatial arrangement has been largely conserved during evolution, especially at small spatial scales. Species in which conduits were aggregated in clusters had a lower conduit density compared to those with uniform distribution. Statistically sound spatial indices must be employed as an aid in the characterization of distributional patterns across species and in models of xylem water transport. Point pattern analysis is a very useful tool in identifying spatial patterns. |
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IAM; |
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IAM @ iam @ MMG2010 |
Serial |
1623 |
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Author |
Victor Ponce; Mario Gorga; Xavier Baro; Petia Radeva; Sergio Escalera |
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Title |
Analisis de la Expresion Oral y Gestual en Proyectos Fin de Carrera Via un Sistema de Vision Artificial |
Type |
Miscellaneous |
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Year |
2011 |
Publication |
Revista electronica de la asociacion de enseñantes universitarios de la informatica AENUI |
Abbreviated Journal |
ReVision |
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Volume |
4 |
Issue |
1 |
Pages |
8-18 |
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La comunicación y expresión oral es una competencia de especial relevancia en el EEES. No obstante, en muchas enseñanzas superiores la puesta en práctica de esta competencia ha sido relegada principalmente a la presentación de proyectos fin de carrera. Dentro de un proyecto de innovación docente, se ha desarrollado una herramienta informática para la extracción de información objetiva para el análisis de la expresión oral y gestual de los alumnos. El objetivo es dar un “feedback” a los estudiantes que les permita mejorar la calidad de sus presentaciones. El prototipo inicial que se presenta en este trabajo permite extraer de forma automática información audiovisual y analizarla mediante técnicas de aprendizaje. El sistema ha sido aplicado a 15 proyectos fin de carrera y 15 exposiciones dentro de una asignatura de cuarto curso. Los resultados obtenidos muestran la viabilidad del sistema para sugerir factores que ayuden tanto en el éxito de la comunicación así como en los criterios de evaluación. |
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1989-1199 |
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MILAB;HuPBA;MV |
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no |
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Admin @ si @ PGB2011c |
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1783 |
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Author |
Victor Ponce; Mario Gorga; Xavier Baro; Petia Radeva; Sergio Escalera |
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Title |
Análisis de la expresión oral y gestual en proyectos fin de carrera vía un sistema de visión artificial |
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Journal Article |
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Year |
2011 |
Publication |
ReVisión |
Abbreviated Journal |
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4 |
Issue |
1 |
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Abstract |
La comunicación y expresión oral es una competencia de especial relevancia en el EEES. No obstante, en muchas enseñanzas superiores la puesta en práctica de esta competencia ha sido relegada principalmente a la presentación de proyectos fin de carrera. Dentro de un proyecto de innovación docente, se ha desarrollado una herramienta informática para la extracción de información objetiva para el análisis de la expresión oral y gestual de los alumnos. El objetivo es dar un “feedback” a los estudiantes que les permita mejorar la calidad de sus presentaciones. El prototipo inicial que se presenta en este trabajo permite extraer de forma automática información audiovisual y analizarla mediante técnicas de aprendizaje. El sistema ha sido aplicado a 15 proyectos fin de carrera y 15 exposiciones dentro de una asignatura de cuarto curso. Los resultados obtenidos muestran la viabilidad del sistema para sugerir factores que ayuden tanto en el éxito de la comunicación así como en los criterios de evaluación. |
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1989-1199 |
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Notes |
HuPBA; MILAB;MV |
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no |
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Call Number |
Admin @ si @ PGB2011d |
Serial |
2514 |
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Permanent link to this record |
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Author |
Jorge Bernal; F. Javier Sanchez; Fernando Vilariño |
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Title |
Integration of Valley Orientation Distribution for Polyp Region Identification in Colonoscopy |
Type |
Conference Article |
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Year |
2011 |
Publication |
In MICCAI 2011 Workshop on Computational and Clinical Applications in Abdominal Imaging |
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Volume |
6668 |
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Pages |
76-83 |
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This work presents a region descriptor based on the integration of the information that the depth of valleys image provides. The depth of valleys image is based on the presence of intensity valleys around polyps due to the image acquisition. Our proposed method consists of defining, for each point, a series of radial sectors around it and then accumulates the maxima of the depth of valleys image only if the orientation of the intensity valley coincides with the orientation of the sector above. We apply our descriptor to a prior segmentation of the images and we present promising results on polyp detection, outperforming other approaches that also integrate depth of valleys information. |
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Toronto, Canada |
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Springer Link |
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Lecture Notes in Computer Science |
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800 |
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ABI |
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MV;SIAI |
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no |
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IAM @ iam @ BSV2011d |
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1698 |
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Author |
Gemma Rotger; Francesc Moreno-Noguer; Felipe Lumbreras; Antonio Agudo |
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Title |
Detailed 3D face reconstruction from a single RGB image |
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Journal |
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Year |
2019 |
Publication |
Journal of WSCG |
Abbreviated Journal |
JWSCG |
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27 |
Issue |
2 |
Pages |
103-112 |
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Keywords |
3D Wrinkle Reconstruction; Face Analysis, Optimization. |
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This paper introduces a method to obtain a detailed 3D reconstruction of facial skin from a single RGB image.
To this end, we propose the exclusive use of an input image without requiring any information about the observed material nor training data to model the wrinkle properties. They are detected and characterized directly from the image via a simple and effective parametric model, determining several features such as location, orientation, width, and height. With these ingredients, we propose to minimize a photometric error to retrieve the final detailed 3D map, which is initialized by current techniques based on deep learning. In contrast with other approaches, we only require estimating a depth parameter, making our approach fast and intuitive. Extensive experimental evaluation is presented in a wide variety of synthetic and real images, including different skin properties and facial
expressions. In all cases, our method outperforms the current approaches regarding 3D reconstruction accuracy, providing striking results for both large and fine wrinkles. |
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2019/11 |
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MSIAU; 600.086; 600.130; 600.122 |
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no |
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Admin @ si @ |
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3708 |
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Author |
Patricia Marquez; Debora Gil; Aura Hernandez-Sabate; Daniel Kondermann |
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Title |
When Is A Confidence Measure Good Enough? |
Type |
Conference Article |
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Year |
2013 |
Publication |
9th International Conference on Computer Vision Systems |
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7963 |
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344-353 |
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Optical flow, confidence measure, performance evaluation |
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Abstract |
Confidence estimation has recently become a hot topic in image processing and computer vision.Yet, several definitions exist of the term “confidence” which are sometimes used interchangeably. This is a position paper, in which we aim to give an overview on existing definitions,
thereby clarifying the meaning of the used terms to facilitate further research in this field. Based on these clarifications, we develop a theory to compare confidence measures with respect to their quality. |
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St Petersburg; Russia; July 2013 |
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Springer Link |
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LNCS |
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ISSN |
0302-9743 |
ISBN |
978-3-642-39401-0 |
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ICVS |
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IAM;ADAS; 600.044; 600.057; 600.060; 601.145 |
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no |
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IAM @ iam @ MGH2013a |
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2218 |
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Author |
Zhengying Liu; Zhen Xu; Shangeth Rajaa; Meysam Madadi; Julio C. S. Jacques Junior; Sergio Escalera; Adrien Pavao; Sebastien Treguer; Wei-Wei Tu; Isabelle Guyon |
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Title |
Towards Automated Deep Learning: Analysis of the AutoDL challenge series 2019 |
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Conference Article |
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2020 |
Publication |
Proceedings of Machine Learning Research |
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123 |
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242-252 |
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We present the design and results of recent competitions in Automated Deep Learning (AutoDL). In the AutoDL challenge series 2019, we organized 5 machine learning challenges: AutoCV, AutoCV2, AutoNLP, AutoSpeech and AutoDL. The first 4 challenges concern each a specific application domain, such as computer vision, natural language processing and speech recognition. At the time of March 2020, the last challenge AutoDL is still on-going and we only present its design. Some highlights of this work include: (1) a benchmark suite of baseline AutoML solutions, with emphasis on domains for which Deep Learning methods have had prior success (image, video, text, speech, etc); (2) a novel any-time learning framework, which opens doors for further theoretical consideration; (3) a repository of around 100 datasets (from all above domains) over half of which are released as public datasets to enable research on meta-learning; (4) analyses revealing that winning solutions generalize to new unseen datasets, validating progress towards universal AutoML solution; (5) open-sourcing of the challenge platform, the starting kit, the dataset formatting toolkit, and all winning solutions (All information available at {autodl.chalearn.org}). |
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NEURIPS |
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HUPBA |
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no |
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Admin @ si @ LXR2020 |
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3500 |
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Author |
Josep Llados; Ernest Valveny; Gemma Sanchez; Enric Marti |
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Title |
Symbol recognition: current advances and perspectives |
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Book Chapter |
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2002 |
Publication |
Graphics Recognition Algorithms And Applications |
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LNCS |
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2390 |
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104-128 |
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The recognition of symbols in graphic documents is an intensive research activity in the community of pattern recognition and document analysis. A key issue in the interpretation of maps, engineering drawings, diagrams, etc. is the recognition of domain dependent symbols according to a symbol database. In this work we first review the most outstanding symbol recognition methods from two different points of view: application domains and pattern recognition methods. In the second part of the paper, open and unaddressed problems involved in symbol recognition are described, analyzing their current state of art and discussing future research challenges. Thus, issues such as symbol representation, matching, segmentation, learning, scalability of recognition methods and performance evaluation are addressed in this work. Finally, we discuss the perspectives of symbol recognition concerning to new paradigms such as user interfaces in handheld computers or document database and WWW indexing by graphical content. |
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London, UK |
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Springer-Verlag |
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Dorothea Blostein and Young- Bin Kwon |
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Lecture Notes in Computer Science |
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LNCS |
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3-540-44066-6 |
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GREC |
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Notes |
DAG; IAM; |
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no |
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IAM @ iam @ LVS2002 |
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1572 |
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Author |
Josep Llados;Horst Bunke; Enric Marti |
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Title |
Using Cyclic String Matching to Find Rotational and Reflectional Symmetries in Shapes |
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Conference Article |
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Year |
1997 |
Publication |
Intelligent Robots: Sensing, Modeling and Planning |
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164-179 |
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Abstract |
Dagstuhl Workshop |
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World Scientific Press |
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9810231857 |
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DAG;IAM; |
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IAM @ iam @ LBM1997b |
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1563 |
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Author |
Joel Barajas; Jaume Garcia; Francesc Carreras; Sandra Pujades; Petia Radeva |
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Title |
Angle Images Using Gabor Filters in Cardiac Tagged MRI |
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Conference Article |
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2005 |
Publication |
Proceeding of the 2005 conference on Artificial Intelligence Research and Development |
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107-114 |
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Keywords |
Angle Images, Gabor Filters, Harp, Tagged Mri |
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Abstract |
Tagged Magnetic Resonance Imaging (MRI) is a non-invasive technique used to examine cardiac deformation in vivo. An Angle Image is a representation of a Tagged MRI which recovers the relative position of the tissue respect to the distorted tags. Thus cardiac deformation can be estimated. This paper describes a new approach to generate Angle Images using a bank of Gabor filters in short axis cardiac Tagged MRI. Our method improves the Angle Images obtained by global techniques, like HARP, with a local frequency analysis. We propose to use the phase response of a combination of a Gabor filters bank, and use it to find a more precise deformation of the left ventricle. We demonstrate the accuracy of our method over HARP by several experimental results. |
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Amsterdam; The Netherlands |
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IOS Press |
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Amsterdam, The Netherlands |
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1-58603-560-6 |
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CAIRD |
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IAM;MILAB |
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BCNPCL @ bcnpcl @ BGC2005; IAM @ iam |
Serial |
595 |
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Author |
Enric Marti; Jordi Regincos;Jaime Lopez-Krahe; Juan J.Villanueva |
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Title |
Hand line drawing interpretation as three-dimensional objects |
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Journal Article |
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Year |
1993 |
Publication |
Signal Processing – Intelligent systems for signal and image understanding |
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32 |
Issue |
1-2 |
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91-110 |
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Keywords |
Line drawing interpretation; line labelling; scene analysis; man-machine interaction; CAD input; line extraction |
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Abstract |
In this paper we present a technique to interpret hand line drawings as objects in a three-dimensional space. The object domain considered is based on planar surfaces with straight edges, concretely, on ansextension of Origami world to hidden lines. The line drawing represents the object under orthographic projection and it is sensed using a scanner. Our method is structured in two modules: feature extraction and feature interpretation. In the first one, image processing techniques are applied under certain tolerance margins to detect lines and junctions on the hand line drawing. Feature interpretation module is founded on line labelling techniques using a labelled junction dictionary. A labelling algorithm is here proposed. It uses relaxation techniques to reduce the number of incompatible labels with the junction dictionary so that the convergence of solutions can be accelerated. We formulate some labelling hypotheses tending to eliminate elements in two sets of labelled interpretations. That is, those which are compatible with the dictionary but do not correspond to three-dimensional objects and those which represent objects not very probable to be specified by means of a line drawing. New entities arise on the line drawing as a result of the extension of Origami world. These are defined to enunciate the assumptions of our method as well as to clarify the algorithms proposed. This technique is framed in a project aimed to implement a system to create 3D objects to improve man-machine interaction in CAD systems. |
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Elsevier North-Holland, Inc. |
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Amsterdam, The Netherlands, The Netherlands |
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0165-1684 |
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IAM;ISE; |
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IAM @ iam @ MRL1993 |
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1611 |
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Author |
B. Zhou; Agata Lapedriza; J. Xiao; A. Torralba; A. Oliva |
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Title |
Learning Deep Features for Scene Recognition using Places Database |
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Conference Article |
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2014 |
Publication |
28th Annual Conference on Neural Information Processing Systems |
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487-495 |
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Montreal; Canada; December 2014 |
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NIPS |
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OR;MV |
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Admin @ si @ ZLX2014 |
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2621 |
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