Efficient cost aggregation for feature-vector-based wide-baseline stereo matching
<p dir="ltr">In stereo matching applications, local cost aggregation techniques are usually preferred over global methods due to their speed and ease of implementation. Local methods make implicit smoothness assumptions by aggregating costs within a finite window; however, cost aggre...
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2018
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| _version_ | 1864513512977465344 |
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| author | Xiaoming Peng (16948488) |
| author2 | Abdesselam Bouzerdoum (17900021) Son Lam Phung (18460602) |
| author2_role | author author |
| author_facet | Xiaoming Peng (16948488) Abdesselam Bouzerdoum (17900021) Son Lam Phung (18460602) |
| author_role | author |
| dc.creator.none.fl_str_mv | Xiaoming Peng (16948488) Abdesselam Bouzerdoum (17900021) Son Lam Phung (18460602) |
| dc.date.none.fl_str_mv | 2018-04-11T03:00:00Z |
| dc.identifier.none.fl_str_mv | 10.1186/s13640-018-0249-y |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/Efficient_cost_aggregation_for_feature-vector-based_wide-baseline_stereo_matching/25953601 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Information and computing sciences Computer vision and multimedia computation Stereo matching Cost aggregation Feature vector DAISY |
| dc.title.none.fl_str_mv | Efficient cost aggregation for feature-vector-based wide-baseline stereo matching |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <p dir="ltr">In stereo matching applications, local cost aggregation techniques are usually preferred over global methods due to their speed and ease of implementation. Local methods make implicit smoothness assumptions by aggregating costs within a finite window; however, cost aggregation is a time-consuming process. Furthermore, most existing local methods are based on pixel intensity values, and hence are not efficient with feature vectors used in wide-baseline stereo matching. In this paper, a new cost aggregation method is proposed, where a Per-Column Cost matrix is combined with a feature-vector-based weighting strategy to achieve both matching accuracy and computational efficiency. Here, the proposed cost aggregation method is applied with the DAISY feature descriptor for wide-baseline stereo matching; however, this method can also be applied to a fast growing number of stereo matching techniques that are based on feature descriptors. A performance comparison with several benchmark local cost aggregation approaches is presented, along with a thorough analysis of the time and storage complexity of the proposed method.</p><h2>Other Information</h2><p dir="ltr">Published in: EURASIP Journal on Image and Video Processing<br>License: <a href="https://creativecommons.org/licenses/by/4.0" target="_blank">https://creativecommons.org/licenses/by/4.0</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1186/s13640-018-0249-y" target="_blank">https://dx.doi.org/10.1186/s13640-018-0249-y</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_45a5702698ce019af22a5b6a71cdd50d |
| identifier_str_mv | 10.1186/s13640-018-0249-y |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/25953601 |
| publishDate | 2018 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Efficient cost aggregation for feature-vector-based wide-baseline stereo matchingXiaoming Peng (16948488)Abdesselam Bouzerdoum (17900021)Son Lam Phung (18460602)Information and computing sciencesComputer vision and multimedia computationStereo matchingCost aggregationFeature vectorDAISY<p dir="ltr">In stereo matching applications, local cost aggregation techniques are usually preferred over global methods due to their speed and ease of implementation. Local methods make implicit smoothness assumptions by aggregating costs within a finite window; however, cost aggregation is a time-consuming process. Furthermore, most existing local methods are based on pixel intensity values, and hence are not efficient with feature vectors used in wide-baseline stereo matching. In this paper, a new cost aggregation method is proposed, where a Per-Column Cost matrix is combined with a feature-vector-based weighting strategy to achieve both matching accuracy and computational efficiency. Here, the proposed cost aggregation method is applied with the DAISY feature descriptor for wide-baseline stereo matching; however, this method can also be applied to a fast growing number of stereo matching techniques that are based on feature descriptors. A performance comparison with several benchmark local cost aggregation approaches is presented, along with a thorough analysis of the time and storage complexity of the proposed method.</p><h2>Other Information</h2><p dir="ltr">Published in: EURASIP Journal on Image and Video Processing<br>License: <a href="https://creativecommons.org/licenses/by/4.0" target="_blank">https://creativecommons.org/licenses/by/4.0</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1186/s13640-018-0249-y" target="_blank">https://dx.doi.org/10.1186/s13640-018-0249-y</a></p>2018-04-11T03:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1186/s13640-018-0249-yhttps://figshare.com/articles/journal_contribution/Efficient_cost_aggregation_for_feature-vector-based_wide-baseline_stereo_matching/25953601CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/259536012018-04-11T03:00:00Z |
| spellingShingle | Efficient cost aggregation for feature-vector-based wide-baseline stereo matching Xiaoming Peng (16948488) Information and computing sciences Computer vision and multimedia computation Stereo matching Cost aggregation Feature vector DAISY |
| status_str | publishedVersion |
| title | Efficient cost aggregation for feature-vector-based wide-baseline stereo matching |
| title_full | Efficient cost aggregation for feature-vector-based wide-baseline stereo matching |
| title_fullStr | Efficient cost aggregation for feature-vector-based wide-baseline stereo matching |
| title_full_unstemmed | Efficient cost aggregation for feature-vector-based wide-baseline stereo matching |
| title_short | Efficient cost aggregation for feature-vector-based wide-baseline stereo matching |
| title_sort | Efficient cost aggregation for feature-vector-based wide-baseline stereo matching |
| topic | Information and computing sciences Computer vision and multimedia computation Stereo matching Cost aggregation Feature vector DAISY |