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Author Antonio Hernandez edit  openurl
  Title Pose and Face Recovery via Spatio-temporal GrabCut Human Segmentation Type Report
  Year 2010 Publication CVC Technical Report Abbreviated Journal  
  Volume 153 Issue Pages  
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  Area Expedition Conference  
  Notes HUPBA;MILAB Approved no  
  Call Number Admin @ si @ Her2010 Serial 1347  
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Author Jorge Bernal; Fernando Vilariño; F. Javier Sanchez edit   pdf
openurl 
  Title Feature Detectors and Feature Descriptors: Where We Are Now Type Report
  Year 2010 Publication CVC Technical Report Abbreviated Journal  
  Volume 154 Issue Pages  
  Keywords  
  Abstract Feature Detection and Feature Description are clearly nowadays topics. Many Computer Vision applications rely on the use of several of these techniques in order to extract the most significant aspects of an image so they can help in some tasks such as image retrieval, image registration, object recognition, object categorization and texture classification, among others. In this paper we define what Feature Detection and Description are and then we present an extensive collection of several methods in order to show the different techniques that are being used right now. The aim of this report is to provide a glimpse of what is being used currently in these fields and to serve as a starting point for future endeavours.  
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  Area 800 Expedition Conference  
  Notes MV;SIAI Approved no  
  Call Number Admin @ si @ BVS2010; IAM @ iam @ BVS2010 Serial 1348  
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Author Lluis Pere de las Heras edit  openurl
  Title Syntactic Model for Semantic Document Analysis Type Report
  Year 2010 Publication CVC Technical Report Abbreviated Journal  
  Volume 158 Issue Pages  
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  Notes Approved no  
  Call Number Admin @ si @ Per2010 Serial 1350  
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Author Anjan Dutta edit  openurl
  Title Symbol Spotting in Graphical Documents by Serialized Subgraph Matching Type Report
  Year 2010 Publication CVC Technical Report Abbreviated Journal  
  Volume 159 Issue Pages  
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  Notes DAG Approved no  
  Call Number Admin @ si @ Dut2010 Serial 1351  
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Author Ekain Artola edit  openurl
  Title Human Attention Map Prediction Combining Visual Features Type Report
  Year 2010 Publication CVC Technical Report Abbreviated Journal  
  Volume 160 Issue Pages  
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  Corporate Author Thesis Bachelor's thesis  
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  Notes Approved no  
  Call Number Admin @ si @ Art2010 Serial 1352  
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Author David Fernandez edit  openurl
  Title Handwritten Word Spotting in Old Manuscript Images using Shape Descriptors Type Report
  Year 2010 Publication CVC Technical Report Abbreviated Journal  
  Volume 161 Issue Pages  
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  Notes DAG Approved no  
  Call Number Admin @ si @ Fer2010b Serial 1353  
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Author Jon Almazan edit  openurl
  Title Deforming the Blurred Shape Model for Shape Description and Recognition Type Report
  Year 2010 Publication CVC Technical Report Abbreviated Journal  
  Volume 163 Issue Pages  
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  Notes Approved no  
  Call Number Admin @ si @ Alm2010 Serial 1354  
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Author Nataliya Shapovalova edit  openurl
  Title On Importance of Interaction and Context Type Report
  Year 2010 Publication CVC Technical Report Abbreviated Journal  
  Volume 155 Issue Pages  
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  Notes ISE Approved no  
  Call Number Admin @ si @ Sha2010 Serial 1355  
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Author Zhanwu Xiong edit  openurl
  Title A Pompd Model for Active Camera Control Type Report
  Year 2010 Publication CVC Technical Report Abbreviated Journal  
  Volume 156 Issue Pages  
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  Corporate Author Thesis Master's thesis  
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  Notes ISE Approved no  
  Call Number Admin @ si @ Xio2010 Serial 1356  
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Author Olivier Penacchio; C. Alejandro Parraga; Maria Vanrell edit  openurl
  Title Natural Scene Statistics account for Human Cones Ratios Type Journal Article
  Year 2010 Publication Perception. ECVP Abstract Supplement Abbreviated Journal PER  
  Volume 39 Issue Pages 101  
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  Abstract In two previous experiments [Parraga et al, 2009 J. of Im. Sci. and Tech 53(3) 031106; Benavente et al,2009 Perception 38 ECVP Supplement, 36] the boundaries of basic colour categories were measured.
In the first experiment, samples were presented in isolation (ie on a dark background) and boundaries were measured using a yes/no paradigm. In the second, subjects adjusted the chromaticity of a sample presented on a random Mondrian background to find the boundary between pairs of adjacent colours.
Results from these experiments showed significant di erences but it was not possible to conclude whether this discrepancy was due to the absence/presence of a colourful background or to the di erences in the paradigms used. In this work, we settle this question by repeating the first experiment (ie samples presented on a dark background) using the second paradigm. A comparison of results shows that
although boundary locations are very similar, boundaries measured in context are significantly di erent(more di use) than those measured in isolation (confirmed by a Student’s t-test analysis on the subject’s answers statistical distributions). In addition, we completed the mapping of colour name space by measuring the boundaries between chromatic colours and the achromatic centre. With these results we completed our parametric fuzzy-sets model of colour naming space.		  
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  Notes CIC Approved no  
  Call Number CAT @ cat @ PPV2010 Serial 1357  
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Author Bogdan Raducanu; D. Gatica-Perez edit   pdf
doi  openurl
  Title Inferring competitive role patterns in reality TV show through nonverbal analysis Type Journal Article
  Year 2012 Publication Multimedia Tools and Applications Abbreviated Journal MTAP  
  Volume 56 Issue 1 Pages 207-226  
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  Abstract This paper introduces a new facet of social media, namely that depicting social interaction. More concretely, we address this problem from the perspective of nonverbal behavior-based analysis of competitive meetings. For our study, we made use of “The Apprentice” reality TV show, which features a competition for a real, highly paid corporate job. Our analysis is centered around two tasks regarding a person's role in a meeting: predicting the person with the highest status, and predicting the fired candidates. We address this problem by adopting both supervised and unsupervised strategies. The current study was carried out using nonverbal audio cues. Our approach is based only on the nonverbal interaction dynamics during the meeting without relying on the spoken words. The analysis is based on two types of data: individual and relational measures. Results obtained from the analysis of a full season of the show are promising (up to 85.7% of accuracy in the first case and up to 92.8% in the second case). Our approach has been conveniently compared with the Influence Model, demonstrating its superiority.  
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  Publisher Elsevier Place of Publication Editor  
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  ISSN 1380-7501 ISBN Medium  
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  Notes OR;MV Approved no  
  Call Number BCNPCL @ bcnpcl @ RaG2012 Serial 1360  
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Author Neus Salvatella; E Fernandez-Nofrerias; Francesco Ciompi; Oriol Rodriguez-Leor; H. Tizon; Xavier Carrillo; J. Mauri; Petia Radeva edit  doi
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  Title Radial Artery Volume Changes After Administration Of Two Different Intra-arterial Drug Regimens. Assessment by Intravascular Ultrasound Type Journal Article
  Year 2010 Publication Journal of the American College of Cardiology Abbreviated Journal JACC  
  Volume 56 Issue 13s1 Pages B119  
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  Notes MILAB Approved no  
  Call Number BCNPCL @ bcnpcl @ SFC2010b Serial 1364  
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Author R. de Nijs; Sebastian Ramos; Gemma Roig; Xavier Boix; Luc Van Gool; K. Kühnlenz. edit   pdf
openurl 
  Title On-line Semantic Perception Using Uncertainty Type Conference Article
  Year 2012 Publication International Conference on Intelligent Robots and Systems Abbreviated Journal IROS  
  Volume Issue Pages 4185-4191  
  Keywords Semantic Segmentation  
  Abstract Visual perception capabilities are still highly unreliable in unconstrained settings, and solutions might not beaccurate in all regions of an image. Awareness of the uncertainty of perception is a fundamental requirement for proper high level decision making in a robotic system. Yet, the uncertainty measure is often sacrificed to account for dependencies between object/region classifiers. This is the case of Conditional Random Fields (CRFs), the success of which stems from their ability to infer the most likely world configuration, but they do not directly allow to estimate the uncertainty of the solution. In this paper, we consider the setting of assigning semantic labels to the pixels of an image sequence. Instead of using a CRF, we employ a Perturb-and-MAP Random Field, a recently introduced probabilistic model that allows performing fast approximate sampling from its probability density function. This allows to effectively compute the uncertainty of the solution, indicating the reliability of the most likely labeling in each region of the image. We report results on the CamVid dataset, a standard benchmark for semantic labeling of urban image sequences. In our experiments, we show the benefits of exploiting the uncertainty by putting more computational effort on the regions of the image that are less reliable, and use more efficient techniques for other regions, showing little decrease of performance  
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  Area Expedition Conference IROS  
  Notes ADAS Approved no  
  Call Number ADAS @ adas @ NRR2012 Serial 2378  
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Author Daniel Ponsa; Joan Serrat; Antonio Lopez edit   pdf
doi  openurl
  Title On-board image-based vehicle detection and tracking Type Journal Article
  Year 2011 Publication Transactions of the Institute of Measurement and Control Abbreviated Journal TIM  
  Volume 33 Issue 7 Pages 783-805  
  Keywords vehicle detection  
  Abstract In this paper we present a computer vision system for daytime vehicle detection and localization, an essential step in the development of several types of advanced driver assistance systems. It has a reduced processing time and high accuracy thanks to the combination of vehicle detection with lane-markings estimation and temporal tracking of both vehicles and lane markings. Concerning vehicle detection, our main contribution is a frame scanning process that inspects images according to the geometry of image formation, and with an Adaboost-based detector that is robust to the variability in the different vehicle types (car, van, truck) and lighting conditions. In addition, we propose a new method to estimate the most likely three-dimensional locations of vehicles on the road ahead. With regards to the lane-markings estimation component, we have two main contributions. First, we employ a different image feature to the other commonly used edges: we use ridges, which are better suited to this problem. Second, we adapt RANSAC, a generic robust estimation method, to fit a parametric model of a pair of lane markings to the image features. We qualitatively assess our vehicle detection system in sequences captured on several road types and under very different lighting conditions. The processed videos are available on a web page associated with this paper. A quantitative evaluation of the system has shown quite accurate results (a low number of false positives and negatives) at a reasonable computation time.  
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  Notes ADAS Approved no  
  Call Number ADAS @ adas @ PSL2011 Serial 1413  
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Author Jaume Gibert; Ernest Valveny edit  doi
isbn  openurl
  Title Graph Embedding based on Nodes Attributes Representatives and a Graph of Words Representation. Type Conference Article
  Year 2010 Publication 13th International worshop on structural and syntactic pattern recognition and 8th international worshop on statistical pattern recognition Abbreviated Journal  
  Volume 6218 Issue Pages 223–232  
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  Abstract Although graph embedding has recently been used to extend statistical pattern recognition techniques to the graph domain, some existing embeddings are usually computationally expensive as they rely on classical graph-based operations. In this paper we present a new way to embed graphs into vector spaces by first encapsulating the information stored in the original graph under another graph representation by clustering the attributes of the graphs to be processed. This new representation makes the association of graphs to vectors an easy step by just arranging both node attributes and the adjacency matrix in the form of vectors. To test our method, we use two different databases of graphs whose nodes attributes are of different nature. A comparison with a reference method permits to show that this new embedding is better in terms of classification rates, while being much more faster.  
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  Publisher Springer Berlin Heidelberg Place of Publication Editor In E.R. Hancock, R.C. Wilson, T. Windeatt, I. Ulusoy and F. Escolano,  
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  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-14979-5 Medium  
  Area Expedition Conference S+SSPR  
  Notes DAG Approved no  
  Call Number DAG @ dag @ GiV2010 Serial 1416  
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