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Author |
J. Pladellorens; M.J. Yzuel; J. Castell; Joan Serrat |
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Title |
Calculo automatico del volumen del ventriculo izquierdo. Comparacion con expertos. |
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1993 |
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Optica Pura y Aplicada. |
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26 |
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3 |
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685–691 |
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ADAS @ adas @ PYC1993 |
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149 |
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Author |
Daniel Ponsa; Robert Benavente; Felipe Lumbreras; J. Martinez; Xavier Roca |
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Title |
Quality control of safety belts by machine vision inspection for real-time production |
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2003 |
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Optical Engineering, 42:1114–1120 (IF: 0.877) |
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ADAS;ISE;CIC |
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ADAS @ adas @ PRL2003 |
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399 |
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Author |
Daniel Ponsa; Antonio Lopez |
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Title |
Variance reduction techniques in particle-based visual contour Tracking |
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2009 |
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Pattern Recognition |
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PR |
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42 |
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11 |
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2372–2391 |
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Contour tracking; Active shape models; Kalman filter; Particle filter; Importance sampling; Unscented particle filter; Rao-Blackwellization; Partitioned sampling |
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This paper presents a comparative study of three different strategies to improve the performance of particle filters, in the context of visual contour tracking: the unscented particle filter, the Rao-Blackwellized particle filter, and the partitioned sampling technique. The tracking problem analyzed is the joint estimation of the global and local transformation of the outline of a given target, represented following the active shape model approach. The main contributions of the paper are the novel adaptations of the considered techniques on this generic problem, and the quantitative assessment of their performance in extensive experimental work done. |
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ADAS @ adas @ PoL2009a |
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1168 |
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Debora Gil; Aura Hernandez-Sabate; Mireia Brunat;Steven Jansen; Jordi Martinez-Vilalta |
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Title |
Structure-preserving smoothing of biomedical images |
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2011 |
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Pattern Recognition |
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PR |
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44 |
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9 |
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1842-1851 |
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Non-linear smoothing; Differential geometry; Anatomical structures; segmentation; Cardiac magnetic resonance; Computerized tomography |
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Smoothing of biomedical images should preserve gray-level transitions between adjacent tissues, while restoring contours consistent with anatomical structures. Anisotropic diffusion operators are based on image appearance discontinuities (either local or contextual) and might fail at weak inter-tissue transitions. Meanwhile, the output of block-wise and morphological operations is prone to present a block structure due to the shape and size of the considered pixel neighborhood. In this contribution, we use differential geometry concepts to define a diffusion operator that restricts to image consistent level-sets. In this manner, the final state is a non-uniform intensity image presenting homogeneous inter-tissue transitions along anatomical structures, while smoothing intra-structure texture. Experiments on different types of medical images (magnetic resonance, computerized tomography) illustrate its benefit on a further process (such as segmentation) of images. |
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0031-3203 |
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IAM; ADAS |
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IAM @ iam @ GHB2011 |
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1526 |
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Marçal Rusiñol; David Aldavert; Ricardo Toledo; Josep Llados |
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Title |
Efficient segmentation-free keyword spotting in historical document collections |
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2015 |
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Pattern Recognition |
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PR |
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48 |
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2 |
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545–555 |
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Historical documents; Keyword spotting; Segmentation-free; Dense SIFT features; Latent semantic analysis; Product quantization |
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In this paper we present an efficient segmentation-free word spotting method, applied in the context of historical document collections, that follows the query-by-example paradigm. We use a patch-based framework where local patches are described by a bag-of-visual-words model powered by SIFT descriptors. By projecting the patch descriptors to a topic space with the latent semantic analysis technique and compressing the descriptors with the product quantization method, we are able to efficiently index the document information both in terms of memory and time. The proposed method is evaluated using four different collections of historical documents achieving good performances on both handwritten and typewritten scenarios. The yielded performances outperform the recent state-of-the-art keyword spotting approaches. |
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DAG; ADAS; 600.076; 600.077; 600.061; 601.223; 602.006; 600.055 |
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Admin @ si @ RAT2015a |
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2544 |
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Author |
A. Pujol; Jordi Vitria; Felipe Lumbreras; Juan J. Villanueva |
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Title |
Topological principal component analysis for face encoding and recognition |
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Year |
2001 |
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Pattern Recognition Letters |
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PRL |
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22 |
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6-7 |
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769–776 |
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IF: 0.552 |
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ADAS;OR;MV |
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ADAS @ adas @ PVL2001 |
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155 |
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Author |
Jaume Amores; Petia Radeva |
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Registration and Retrieval of Highly Elastic Bodies using Contextual Information |
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2005 |
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Pattern Recognition Letters |
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PRL |
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26 |
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11 |
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1720–1731 |
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IF: 1.138 |
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ADAS;MILAB |
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ADAS @ adas @ AmR2005b |
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592 |
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Jaume Amores; N. Sebe; Petia Radeva |
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Boosting the distance estimation: Application to the K-Nearest Neighbor Classifier |
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2006 |
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Pattern Recognition Letters |
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27 |
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3 |
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201–209 |
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ADAS;MILAB |
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ADAS @ adas @ ASR2006 |
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643 |
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Author |
Fadi Dornaika; Angel Sappa |
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Rigid and Non-rigid Face Motion Tracking by Aligning Texture Maps and Stereo 3D Models |
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2007 |
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Pattern Recognition Letters |
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28 |
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15 |
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2116-2126 |
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ADAS @ adas @ DoS2007c |
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877 |
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Fadi Dornaika; Angel Sappa |
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Instantaneous 3D motion from image derivatives using the Least Trimmed Square Regression |
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2009 |
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Pattern Recognition Letters |
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30 |
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5 |
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535–543 |
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This paper presents a new technique to the instantaneous 3D motion estimation. The main contributions are as follows. First, we show that the 3D camera or scene velocity can be retrieved from image derivatives only assuming that the scene contains a dominant plane. Second, we propose a new robust algorithm that simultaneously provides the Least Trimmed Square solution and the percentage of inliers-the non-contaminated data. Experiments on both synthetic and real image sequences demonstrated the effectiveness of the developed method. Those experiments show that the new robust approach can outperform classical robust schemes. |
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Elsevier Science Inc. |
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0167-8655 |
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ADAS @ adas @ DoS2009a |
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1115 |
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