Perceptual grouping by tensor voting: a comparative survey of recent approaches
Tensor voting is a computational framework that addresses the problem of perceptual organisation. It was designed to convey human perception principles into a unified framework that can be adapted to extract visually salient elements from possibly noisy or corrupted images. The original formulation...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Wiley
2015-04-01
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| Series: | IET Computer Vision |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/iet-cvi.2014.0103 |
| _version_ | 1797684838941065216 |
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| author | Emmanuel Maggiori Hugo Luis Manterola Mariana delFresno |
| author_facet | Emmanuel Maggiori Hugo Luis Manterola Mariana delFresno |
| author_sort | Emmanuel Maggiori |
| collection | DOAJ |
| description | Tensor voting is a computational framework that addresses the problem of perceptual organisation. It was designed to convey human perception principles into a unified framework that can be adapted to extract visually salient elements from possibly noisy or corrupted images. The original formulation featured some concerns that made it difficult or impractical to be applied directly. Therefore, several partial or total theoretical reformulations or augmentations have been proposed. These almost parallel publication were presented in different directions, with different priorities and even in a different notation. Thus, the authors observed the need for a coherent description and comparison of the different proposals. This work, after describing the original approach of tensor voting, reviews and explains a number of high impact theoretical modifications in a self‐contained manner and including possible future directions of work. The authors have selected and organised a number of formulations and unified the way the problem is addressed across the different proposals. The aim of this study is to contribute with a modern comprehensive source of information on the theoretical aspects of tensor voting. |
| first_indexed | 2024-03-12T00:36:35Z |
| format | Article |
| id | doaj.art-d2e53e258c56453c93b0605e6981f8a4 |
| institution | Directory Open Access Journal |
| issn | 1751-9632 1751-9640 |
| language | English |
| last_indexed | 2024-03-12T00:36:35Z |
| publishDate | 2015-04-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Computer Vision |
| spelling | doaj.art-d2e53e258c56453c93b0605e6981f8a42023-09-15T09:37:33ZengWileyIET Computer Vision1751-96321751-96402015-04-019225927710.1049/iet-cvi.2014.0103Perceptual grouping by tensor voting: a comparative survey of recent approachesEmmanuel Maggiori0Hugo Luis Manterola1Mariana delFresno2AYIN and STARSInria Sophia Antipolis F‐06902FrancePLADEMAFac. de Cs. ExactasUNCBPAPinto 3997000TandilArgentinaPLADEMAFac. de Cs. ExactasUNCBPAPinto 3997000TandilArgentinaTensor voting is a computational framework that addresses the problem of perceptual organisation. It was designed to convey human perception principles into a unified framework that can be adapted to extract visually salient elements from possibly noisy or corrupted images. The original formulation featured some concerns that made it difficult or impractical to be applied directly. Therefore, several partial or total theoretical reformulations or augmentations have been proposed. These almost parallel publication were presented in different directions, with different priorities and even in a different notation. Thus, the authors observed the need for a coherent description and comparison of the different proposals. This work, after describing the original approach of tensor voting, reviews and explains a number of high impact theoretical modifications in a self‐contained manner and including possible future directions of work. The authors have selected and organised a number of formulations and unified the way the problem is addressed across the different proposals. The aim of this study is to contribute with a modern comprehensive source of information on the theoretical aspects of tensor voting.https://doi.org/10.1049/iet-cvi.2014.0103tensor votingperceptual groupingperceptual organisationhuman perception principlesvisually salient element extractioncorrupted images |
| spellingShingle | Emmanuel Maggiori Hugo Luis Manterola Mariana delFresno Perceptual grouping by tensor voting: a comparative survey of recent approaches IET Computer Vision tensor voting perceptual grouping perceptual organisation human perception principles visually salient element extraction corrupted images |
| title | Perceptual grouping by tensor voting: a comparative survey of recent approaches |
| title_full | Perceptual grouping by tensor voting: a comparative survey of recent approaches |
| title_fullStr | Perceptual grouping by tensor voting: a comparative survey of recent approaches |
| title_full_unstemmed | Perceptual grouping by tensor voting: a comparative survey of recent approaches |
| title_short | Perceptual grouping by tensor voting: a comparative survey of recent approaches |
| title_sort | perceptual grouping by tensor voting a comparative survey of recent approaches |
| topic | tensor voting perceptual grouping perceptual organisation human perception principles visually salient element extraction corrupted images |
| url | https://doi.org/10.1049/iet-cvi.2014.0103 |
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