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| Author | David Aldavert; Marçal Rusiñol; Ricardo Toledo; Josep Llados | ||||
| Title | Integrating Visual and Textual Cues for Query-by-String Word Spotting | Type | Conference Article | ||
| Year | 2013 | Publication | 12th International Conference on Document Analysis and Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | 511 - 515 | ||
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| Abstract | In this paper, we present a word spotting framework that follows the query-by-string paradigm where word images are represented both by textual and visual representations. The textual representation is formulated in terms of character $n$-grams while the visual one is based on the bag-of-visual-words scheme. These two representations are merged together and projected to a sub-vector space. This transform allows to, given a textual query, retrieve word instances that were only represented by the visual modality. Moreover, this statistical representation can be used together with state-of-the-art indexation structures in order to deal with large-scale scenarios. The proposed method is evaluated using a collection of historical documents outperforming state-of-the-art performances. | ||||
| Address | Washington; USA; August 2013 | ||||
| Corporate Author | Thesis | ||||
| Publisher | Place of Publication | Editor | |||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 1520-5363 | ISBN | Medium | ||
| Area | Expedition  |
Conference | ICDAR | ||
| Notes | DAG; ADAS; 600.045; 600.055; 600.061 | Approved | no | ||
| Call Number | Admin @ si @ ART2013 | Serial | 2224 | ||
| Permanent link to this record | |||||
| Author | David Aldavert; Marçal Rusiñol; Ricardo Toledo; Josep Llados | ||||
| Title | A Study of Bag-of-Visual-Words Representations for Handwritten Keyword Spotting | Type | Journal Article | ||
| Year | 2015 | Publication | International Journal on Document Analysis and Recognition | Abbreviated Journal | IJDAR |
| Volume | 18 | Issue | 3 | Pages | 223-234 |
| Keywords | Bag-of-Visual-Words; Keyword spotting; Handwritten documents; Performance evaluation | ||||
| 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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| Corporate Author | Thesis | ||||
| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 1433-2833 | ISBN | Medium | ||
| Area | Expedition |
Conference | |||
| Notes | DAG; ADAS; 600.055; 600.061; 601.223; 600.077; 600.097 | Approved | no | ||
| Call Number | Admin @ si @ ART2015 | Serial | 2679 | ||
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