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Hugo Jair Escalante; Victor Ponce; Sergio Escalera; Xavier Baro; Alicia Morales-Reyes; Jose Martinez-Carranza |
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Title |
Evolving weighting schemes for the Bag of Visual Words |
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Journal Article |
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2017 |
Publication |
Neural Computing and Applications |
Abbreviated Journal |
Neural Computing and Applications |
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28 |
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5 |
Pages ![sorted by First Page field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
925–939 |
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Bag of Visual Words; Bag of features; Genetic programming; Term-weighting schemes; Computer vision |
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The Bag of Visual Words (BoVW) is an established representation in computer vision. Taking inspiration from text mining, this representation has proved
to be very effective in many domains. However, in most cases, standard term-weighting schemes are adopted (e.g.,term-frequency or TF-IDF). It remains open the question of whether alternative weighting schemes could boost the
performance of methods based on BoVW. More importantly, it is unknown whether it is possible to automatically learn and determine effective weighting schemes from
scratch. This paper brings some light into both of these unknowns. On the one hand, we report an evaluation of the most common weighting schemes used in text mining, but rarely used in computer vision tasks. Besides, we propose an evolutionary algorithm capable of automatically learning weighting schemes for computer vision problems. We report empirical results of an extensive study in several computer vision problems. Results show the usefulness of the proposed method. |
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HUPBA;MV; no menciona |
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no |
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Admin @ si @ EPE2017 |
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2743 |
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Author |
Fadi Dornaika; Bogdan Raducanu |
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Title |
Three-Dimensional Face Pose Detection and Tracking Using Monocular Videos: Tool and Application |
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Journal Article |
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2009 |
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IEEE Transactions on Systems, Man and Cybernetics part B |
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TSMCB |
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39 |
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4 |
Pages ![sorted by First Page field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
935–944 |
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Recently, we have proposed a real-time tracker that simultaneously tracks the 3-D head pose and facial actions in monocular video sequences that can be provided by low quality cameras. This paper has two main contributions. First, we propose an automatic 3-D face pose initialization scheme for the real-time tracker by adopting a 2-D face detector and an eigenface system. Second, we use the proposed methods-the initialization and tracking-for enhancing the human-machine interaction functionality of an AIBO robot. More precisely, we show how the orientation of the robot's camera (or any active vision system) can be controlled through the estimation of the user's head pose. Applications based on head-pose imitation such as telepresence, virtual reality, and video games can directly exploit the proposed techniques. Experiments on real videos confirm the robustness and usefulness of the proposed methods. |
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BCNPCL @ bcnpcl @ DoR2009a |
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1218 |
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Author |
Carles Sanchez; Jorge Bernal; F. Javier Sanchez; Antoni Rosell; Marta Diez-Ferrer; Debora Gil |
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Title |
Towards On-line Quantification of Tracheal Stenosis from Videobronchoscopy |
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2015 |
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International Journal of Computer Assisted Radiology and Surgery |
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IJCAR |
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10 |
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6 |
Pages ![sorted by First Page field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
935-945 |
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IAM; MV; 600.075 |
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Admin @ si @ SBS2015a |
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2611 |
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Author |
Bogdan Raducanu; Jordi Vitria |
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Title |
Learning to Learn: From Smarts Machines to Intelligent Machines |
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2008 |
Publication |
Patter Recognition Letters |
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PRL |
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29 |
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8 |
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1024–1032 |
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OR;MV |
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BCNPCL @ bcnpcl @ RaV2008a |
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950 |
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Author |
Bogdan Raducanu; Jordi Vitria; Ales Leonardis |
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Title |
Online pattern recognition and machine learning techniques for computer-vision: Theory and applications |
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Journal Article |
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2010 |
Publication |
Image and Vision Computing |
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IMAVIS |
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28 |
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7 |
Pages ![sorted by First Page field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
1063–1064 |
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(Editorial for the Special Issue on Online pattern recognition and machine learning techniques)
In real life, visual learning is supposed to be a continuous process. This paradigm has found its way also in artificial vision systems. There is an increasing trend in pattern recognition represented by online learning approaches, which aims at continuously updating the data representation when new information arrives. Starting with a minimal dataset, the initial knowledge is expanded by incorporating incoming instances, which may have not been previously available or foreseen at the system’s design stage. An interesting characteristic of this strategy is that the train and test phases take place simultaneously. Given the increasing interest in this subject, the aim of this special issue is to be a landmark event in the development of online learning techniques and their applications with the hope that it will capture the interest of a wider audience and will attract even more researchers. We received 19 contributions, of which 9 have been accepted for publication, after having been subjected to usual peer review process. |
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Elsevier |
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0262-8856 |
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OR;MV |
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BCNPCL @ bcnpcl @ RVL2010 |
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1280 |
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