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Author |
David Aldavert; Marçal Rusiñol; Ricardo Toledo; Josep Llados |
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Title |
A Study of Bag-of-Visual-Words Representations for Handwritten Keyword Spotting |
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Journal Article |
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Year |
2015 |
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International Journal on Document Analysis and Recognition |
Abbreviated Journal |
IJDAR |
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Volume |
18 |
Issue |
3 |
Pages |
223-234 |
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Bag-of-Visual-Words; Keyword spotting; Handwritten documents; Performance evaluation |
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Abstract |
The Bag-of-Visual-Words (BoVW) framework has gained popularity among the document image analysis community, specifically as a representation of handwritten words for recognition or spotting purposes. Although in the computer vision field the BoVW method has been greatly improved, most of the approaches in the document image analysis domain still rely on the basic implementation of the BoVW method disregarding such latest refinements. In this paper, we present a review of those improvements and its application to the keyword spotting task. We thoroughly evaluate their impact against a baseline system in the well-known George Washington dataset and compare the obtained results against nine state-of-the-art keyword spotting methods. In addition, we also compare both the baseline and improved systems with the methods presented at the Handwritten Keyword Spotting Competition 2014. |
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Springer Berlin Heidelberg |
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1433-2833 |
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DAG; ADAS; 600.055; 600.061; 601.223; 600.077; 600.097 |
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no |
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Admin @ si @ ART2015 |
Serial |
2679 |
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Author |
Fahad Shahbaz Khan; Muhammad Anwer Rao; Joost Van de Weijer; Andrew Bagdanov; Antonio Lopez; Michael Felsberg |
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Title |
Coloring Action Recognition in Still Images |
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Journal Article |
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Year |
2013 |
Publication |
International Journal of Computer Vision |
Abbreviated Journal |
IJCV |
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Volume |
105 |
Issue |
3 |
Pages |
205-221 |
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In this article we investigate the problem of human action recognition in static images. By action recognition we intend a class of problems which includes both action classification and action detection (i.e. simultaneous localization and classification). Bag-of-words image representations yield promising results for action classification, and deformable part models perform very well object detection. The representations for action recognition typically use only shape cues and ignore color information. Inspired by the recent success of color in image classification and object detection, we investigate the potential of color for action classification and detection in static images. We perform a comprehensive evaluation of color descriptors and fusion approaches for action recognition. Experiments were conducted on the three datasets most used for benchmarking action recognition in still images: Willow, PASCAL VOC 2010 and Stanford-40. Our experiments demonstrate that incorporating color information considerably improves recognition performance, and that a descriptor based on color names outperforms pure color descriptors. Our experiments demonstrate that late fusion of color and shape information outperforms other approaches on action recognition. Finally, we show that the different color–shape fusion approaches result in complementary information and combining them yields state-of-the-art performance for action classification. |
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Springer US |
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0920-5691 |
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CIC; ADAS; 600.057; 600.048 |
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Admin @ si @ KRW2013 |
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2285 |
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Author |
Xavier Boix; Josep M. Gonfaus; Joost Van de Weijer; Andrew Bagdanov; Joan Serrat; Jordi Gonzalez |
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Title |
Harmony Potentials: Fusing Global and Local Scale for Semantic Image Segmentation |
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Journal Article |
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Year |
2012 |
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International Journal of Computer Vision |
Abbreviated Journal |
IJCV |
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96 |
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1 |
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83-102 |
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The Hierarchical Conditional Random Field(HCRF) model have been successfully applied to a number of image labeling problems, including image segmentation. However, existing HCRF models of image segmentation do not allow multiple classes to be assigned to a single region, which limits their ability to incorporate contextual information across multiple scales.
At higher scales in the image, this representation yields an oversimpli ed model since multiple classes can be reasonably expected to appear within large regions. This simpli ed model particularly limits the impact of information at higher scales. Since class-label information at these scales is usually more reliable than at lower, noisier scales, neglecting this information is undesirable. To
address these issues, we propose a new consistency potential for image labeling problems, which we call the harmony potential. It can encode any possible combi-
nation of labels, penalizing only unlikely combinations of classes. We also propose an e ective sampling strategy over this expanded label set that renders tractable the underlying optimization problem. Our approach obtains state-of-the-art results on two challenging, standard benchmark datasets for semantic image segmentation: PASCAL VOC 2010, and MSRC-21. |
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0920-5691 |
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CAT;ISE;CIC;ADAS |
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Call Number |
Admin @ si @ BGW2012 |
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1718 |
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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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Journal Article |
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Year |
2001 |
Publication |
Pattern Recognition Letters |
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PRL |
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22 |
Issue |
6-7 |
Pages |
769–776 |
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Abstract |
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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Title |
Registration and Retrieval of Highly Elastic Bodies using Contextual Information |
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Journal Article |
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Year |
2005 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
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Volume |
26 |
Issue |
11 |
Pages |
1720–1731 |
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Abstract |
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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Author |
Jaume Amores; Petia Radeva |
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Title |
Retrieval of IVUS Images Using Contextual Information and Elastic Matching |
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2005 |
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International Journal on Intelligent Systems, 20(5):541–560 (IF: 0.657) |
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ADAS;MILAB |
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ADAS @ adas @ AmR2005a |
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593 |
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Author |
Jaume Amores; N. Sebe; Petia Radeva |
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Title |
Boosting the distance estimation: Application to the K-Nearest Neighbor Classifier |
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Journal Article |
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Year |
2006 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
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Volume |
27 |
Issue |
3 |
Pages |
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 |
Jaume Amores; N. Sebe; Petia Radeva |
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Title |
Context-Based Object-Class Recognition and Retrieval by Generalized Correlograms |
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2007 |
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IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 29(10):1818–1833, (ISI 3,81) |
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ADAS;MILAB |
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ADAS @ adas @ ASR2007b |
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922 |
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Author |
Yu Jie; Jaume Amores; N. Sebe; Petia Radeva; Tian Qi |
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Title |
Distance Learning for Similarity Estimation |
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2008 |
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IEEE Trans. on Pattern Analysis and Machine Intelligence, vol.30(3):451–462 |
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ADAS @ adas @ JAS2008 |
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961 |
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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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