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Misael Rosales; Petia Radeva; J. Mauri; Oriol Pujol |
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Title  |
Simulation Model of Intravascular Ultrasound Images |
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2004 |
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MICCAI, 2004, Saint Melo, France |
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Springer Verlag |
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MILAB;HuPBA |
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BCNPCL @ bcnpcl @ RRM2004b |
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464 |
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Author |
Fadi Dornaika; Bogdan Raducanu |
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Simultaneous 3D face pose and person-specific shape estimation from a single image using a holistic approach |
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2009 |
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IEEE Workshop on Applications of Computer Vision |
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This paper presents a new approach for the simultaneous estimation of the 3D pose and specific shape of a previously unseen face from a single image. The face pose is not limited to a frontal view. We describe a holistic approach based on a deformable 3D model and a learned statistical facial texture model. Rather than obtaining a person-specific facial surface, the goal of this work is to compute person-specific 3D face shape in terms of a few control parameters that are used by many applications. The proposed holistic approach estimates the 3D pose parameters as well as the face shape control parameters by registering the warped texture to a statistical face texture, which is carried out by a stochastic and genetic optimizer. The proposed approach has several features that make it very attractive: (i) it uses a single grey-scale image, (ii) it is person-independent, (iii) it is featureless (no facial feature extraction is required), and (iv) its learning stage is easy. The proposed approach lends itself nicely to 3D face tracking and face gesture recognition in monocular videos. We describe extensive experiments that show the feasibility and robustness of the proposed approach. |
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Utah, USA |
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1550-5790 |
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978-1-4244-5497-6 |
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WACV |
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OR;MV |
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BCNPCL @ bcnpcl @ DoR2009b |
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1256 |
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Author |
R. Herault; Franck Davoine; Fadi Dornaika; Y. Grandvalet |
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Title |
Simultaneous and robust face and facial action tracking |
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2006 |
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15eme Congres Francophone AFRIF–AFIA de Reconnaissance des Formes et Intelligence Artificielle (RFIA´06) |
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Tours (France) |
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Admin @ si @ HDD2006 |
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735 |
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E. Serradell; Adriana Romero; R. Leta; Carlo Gatta; Francesc Moreno-Noguer |
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Title |
Simultaneous Correspondence and Non-Rigid 3D Reconstruction of the Coronary Tree from Single X-Ray Images |
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2011 |
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13th IEEE International Conference on Computer Vision |
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850-857 |
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Barcelona |
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ICCV |
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MILAB |
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no |
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Admin @ si @ SRL2011 |
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1803 |
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Author |
Fadi Dornaika; Franck Davoine |
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Title |
Simultaneous Facial Action Tracking and Expression Recognition using a Particle Filter |
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2005 |
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10th IEEE Int. Conference on Computer Vision (ICCV) |
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Beijing (China) |
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no |
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Admin @ si @ DoD2005d |
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581 |
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Author |
Marc Bolaños; Petia Radeva |
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Title |
Simultaneous Food Localization and Recognition |
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2016 |
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23rd International Conference on Pattern Recognition |
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CoRR abs/1604.07953
The development of automatic nutrition diaries, which would allow to keep track objectively of everything we eat, could enable a whole new world of possibilities for people concerned about their nutrition patterns. With this purpose, in this paper we propose the first method for simultaneous food localization and recognition. Our method is based on two main steps, which consist in, first, produce a food activation map on the input image (i.e. heat map of probabilities) for generating bounding boxes proposals and, second, recognize each of the food types or food-related objects present in each bounding box. We demonstrate that our proposal, compared to the most similar problem nowadays – object localization, is able to obtain high precision and reasonable recall levels with only a few bounding boxes. Furthermore, we show that it is applicable to both conventional and egocentric images. |
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Cancun; Mexico; December 2016 |
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ICPR |
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MILAB; no proj |
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no |
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Admin @ si @ BoR2016 |
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2834 |
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Author |
Parichehr Behjati; Pau Rodriguez; Carles Fernandez; Isabelle Hupont; Armin Mehri; Jordi Gonzalez |
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Single image super-resolution based on directional variance attention network |
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2023 |
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Pattern Recognition |
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PR |
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133 |
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108997 |
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Recent advances in single image super-resolution (SISR) explore the power of deep convolutional neural networks (CNNs) to achieve better performance. However, most of the progress has been made by scaling CNN architectures, which usually raise computational demands and memory consumption. This makes modern architectures less applicable in practice. In addition, most CNN-based SR methods do not fully utilize the informative hierarchical features that are helpful for final image recovery. In order to address these issues, we propose a directional variance attention network (DiVANet), a computationally efficient yet accurate network for SISR. Specifically, we introduce a novel directional variance attention (DiVA) mechanism to capture long-range spatial dependencies and exploit inter-channel dependencies simultaneously for more discriminative representations. Furthermore, we propose a residual attention feature group (RAFG) for parallelizing attention and residual block computation. The output of each residual block is linearly fused at the RAFG output to provide access to the whole feature hierarchy. In parallel, DiVA extracts most relevant features from the network for improving the final output and preventing information loss along the successive operations inside the network. Experimental results demonstrate the superiority of DiVANet over the state of the art in several datasets, while maintaining relatively low computation and memory footprint. The code is available at https://github.com/pbehjatii/DiVANet. |
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ISE |
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Admin @ si @ BPF2023 |
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3861 |
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Author |
Xavier Soria |
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Title |
Single sensor multi-spectral imaging |
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2019 |
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PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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The image sensor, nowadays, is rolling the smartphone industry. While some phone brands explore equipping more image sensors, others, like Google, maintain their smartphones with just one sensor; but this sensor is equipped with Deep Learning to enhance the image quality. However, what all brands agree on is the need to research new image sensors; for instance, in 2015 Omnivision and PixelTeq presented new CMOS based image sensors defined as multispectral Single Sensor Camera (SSC), which are capable of capturing multispectral bands. This dissertation presents the benefits of using a multispectral SSCs that, as aforementioned, simultaneously acquires images in the visible and near-infrared (NIR) bands. The principal benefits while addressing problems related to image bands in the spectral range of 400 to 1100 nanometers, there are cost reductions in the hardware and software setup because only one SSC is needed instead of two, and the images alignment are not required any more. Concerning to the NIR spectrum, many works in literature have proven the benefits of working with NIR to enhance RGB images (e.g., image enhancement, remove shadows, dehazing, etc.). In spite of the advantage of using SSC (e.g., low latency), there are some drawback to be solved. One of this drawback corresponds to the nature of the silicon-based sensor, which in addition to capture the RGB image, when the infrared cut off filter is not installed it also acquires NIR information into the visible image. This phenomenon is called RGB and NIR crosstalking. This thesis firstly faces this problem in challenging images and then it shows the benefit of using multispectral images in the edge detection task.
The RGB color restoration from RGBN image is the topic tackled in RGB and NIR crosstalking. Even though in the literature a set of processes have been proposed to face this issue, in this thesis novel approaches, based on DL, are proposed to subtract the additional NIR included in the RGB channel. More precisely, an Artificial Neural Network (NN) and two Convolutional Neural Network (CNN) models are proposed. As the DL based models need a dataset with a large collection of image pairs, a large dataset is collected to address the color restoration. The collected images are from challenging scenes where the sunlight radiation is sufficient to give absorption/reflectance properties to the considered scenes. An extensive evaluation has been conducted on the CNN models, differences from most of the restored images are almost imperceptible to the human eye. The next proposal of the thesis is the validation of the usage of SSC images in the edge detection task. Three methods based on CNN have been proposed. While the first one is based on the most used model, holistically-nested edge detection (HED) termed as multispectral HED (MS-HED), the other two have been proposed observing the drawbacks of MS-HED. These two novel architectures have been designed from scratch (training from scratch); after the first architecture is validated in the visible domain a slight redesign is proposed to tackle the multispectral domain. Again, another dataset is collected to face this problem with SSCs. Even though edge detection is confronted in the multispectral domain, its qualitative and quantitative evaluation demonstrates the generalization in other datasets used for edge detection, improving state-of-the-art results. |
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September 2019 |
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Ph.D. thesis |
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Ediciones Graficas Rey |
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Angel Sappa |
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978-84-948531-9-7 |
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MSIAU; 600.122 |
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Admin @ si @ Sor2019 |
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3391 |
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Author |
Lluis Gomez; Andres Mafla; Marçal Rusiñol; Dimosthenis Karatzas |
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Title |
Single Shot Scene Text Retrieval |
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Conference Article |
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2018 |
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15th European Conference on Computer Vision |
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11218 |
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728-744 |
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Image retrieval; Scene text; Word spotting; Convolutional Neural Networks; Region Proposals Networks; PHOC |
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Textual information found in scene images provides high level semantic information about the image and its context and it can be leveraged for better scene understanding. In this paper we address the problem of scene text retrieval: given a text query, the system must return all images containing the queried text. The novelty of the proposed model consists in the usage of a single shot CNN architecture that predicts at the same time bounding boxes and a compact text representation of the words in them. In this way, the text based image retrieval task can be casted as a simple nearest neighbor search of the query text representation over the outputs of the CNN over the entire image
database. Our experiments demonstrate that the proposed architecture
outperforms previous state-of-the-art while it offers a significant increase
in processing speed. |
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Munich; September 2018 |
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ECCV |
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DAG; 600.084; 601.338; 600.121; 600.129 |
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Admin @ si @ GMR2018 |
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3143 |
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Fadi Dornaika; Bogdan Raducanu |
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Single Snapshot 3D Head Pose Initialization for Tracking in Human Robot Interaction Scenario |
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2010 |
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1st International Workshop on Computer Vision for Human-Robot Interaction |
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32–39 |
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1st International Workshop on Computer Vision for Human-Robot Interaction, in conjunction with IEEE CVPR 2010 |
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This paper presents an automatic 3D head pose initialization scheme for a real-time face tracker with application to human-robot interaction. It has two main contributions. First, we propose an automatic 3D head pose and person specific face shape estimation, based on a 3D deformable model. The proposed approach serves to initialize our realtime 3D face tracker. What makes this contribution very attractive is that the initialization step can cope with faces
under arbitrary pose, so it is not limited only to near-frontal views. Second, the previous framework is used to develop an application in which the orientation of an AIBO’s camera can be controlled through the imitation of user’s head pose.
In our scenario, this application is used to build panoramic images from overlapping snapshots. Experiments on real videos confirm the robustness and usefulness of the proposed methods. |
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San Francisco; CA; USA; June 2010 |
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2160-7508 |
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978-1-4244-7029-7 |
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CVPRW |
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OR;MV |
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BCNPCL @ bcnpcl @ DoR2010a |
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1309 |
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Author |
Gemma Rotger; Francesc Moreno-Noguer; Felipe Lumbreras; Antonio Agudo |
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Single view facial hair 3D reconstruction |
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Conference Article |
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2019 |
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9th Iberian Conference on Pattern Recognition and Image Analysis |
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11867 |
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423-436 |
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3D Vision; Shape Reconstruction; Facial Hair Modeling |
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n this work, we introduce a novel energy-based framework that addresses the challenging problem of 3D reconstruction of facial hair from a single RGB image. To this end, we identify hair pixels over the image via texture analysis and then determine individual hair fibers that are modeled by means of a parametric hair model based on 3D helixes. We propose to minimize an energy composed of several terms, in order to adapt the hair parameters that better fit the image detections. The final hairs respond to the resulting fibers after a post-processing step where we encourage further realism. The resulting approach generates realistic facial hair fibers from solely an RGB image without assuming any training data nor user interaction. We provide an experimental evaluation on real-world pictures where several facial hair styles and image conditions are observed, showing consistent results and establishing a comparison with respect to competing approaches. |
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Madrid; July 2019 |
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IbPRIA |
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ADAS; 600.086; 600.130; 600.122 |
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Admin @ si @ |
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3707 |
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Author |
David Geronimo; Antonio Lopez |
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Title |
Sistema de deteccion de peatones |
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Miscellaneous |
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2010 |
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UAB Divulga |
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Durante la próxima década, los sistemas de protección de peatones jugarán un papel fundamental en el reto de mejorar la seguridad viaria. El objetivo principal de estos sistemas, detectar peatones en entornos urbanos, implica procesar imágenes de escenas exteriores desde una plataforma móvil para buscar objetos de aspecto variable como son las personas. Dadas estas dificultades, estos sistemas hacen uso de las últimas técnicas de visión por computador. Esta propuesta consiste en un sistema de tres módulos basado tanto en información 2D como en 3D. El primer módulo utiliza información 3D para hacer una estimación de los parámetros de la carretera y seleccionar regiones de interés que serán analizadas después. El segundo módulo utiliza un clasificador de ventanas 2D para etiquetar las mencionadas regiones como peatón o no peatón. El módulo final vuelve a utilizar de nuevo la información 3D para verificar las regiones clasificadas y, con información 2D, refinar los resultados finales. Los resultados experimentales son positivos tanto en rendimiento como en tiempo de cómputo. |
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Bellaterra (Spain) |
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spreading;ADAS |
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ADAS @ adas @ GeL2010b |
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1473 |
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Author |
Raul Chaves |
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Sistema de identificacion mediante huellas dactilares |
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Report |
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2004 |
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CVC Technical Report #81 |
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Admin @ si @ Cha2004 |
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507 |
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Author |
C. Mariño; V.M. Gulias; M.G. Penas; M. Penedo; Victor Leboran; A. Mosquera; M.J. Carreira; David Lloret |
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Sistema de Interpretacion Automatica de Secuencias solo Basado en un Servidor vod. |
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2001 |
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Proceedings of the SIT2001. |
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no |
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Admin @ si @ MGP2001 |
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196 |
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Author |
Jordi Gonzalez; J. Varona; Xavier Roca; Juan J. Villanueva |
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Title |
Situation Graph Trees for Human Behavior Modeling |
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Miscellaneous |
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2004 |
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7th Catalan Conference for Artificial Intelligence (CCIA’2004) |
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Barcelona (Spain) |
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ISE |
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ISE @ ise @ GVR2004b |
Serial |
498 |
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