A Novel Transferable Sparse Regression Method for Cross-Database Facial Expression Recognition Article Swipe
Wenjing Zhang
,
Peng Song
,
Wenming Zheng
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1587/transinf.2021edl8062
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1587/transinf.2021edl8062
In this letter, we propose a novel transferable sparse regression (TSR) method, for cross-database facial expression recognition (FER). In TSR, we firstly present a novel regression function to regress the data into a latent representation space instead of a strict binary label space. To further alleviate the influence of outliers and overfitting, we impose a row sparsity constraint on the regression term. And a pairwise relation term is introduced to guide the feature transfer learning. Secondly, we design a global graph to transfer knowledge, which can well preserve the cross-database manifold structure. Moreover, we introduce a low-rank constraint on the graph regularization term to uncover additional structural information. Finally, several experiments are conducted on three popular facial expression databases, and the results validate that the proposed TSR method is superior to other non-deep and deep transfer learning methods.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1587/transinf.2021edl8062
- https://www.jstage.jst.go.jp/article/transinf/E105.D/1/E105.D_2021EDL8062/_pdf
- OA Status
- diamond
- References
- 16
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4205661186
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4205661186Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1587/transinf.2021edl8062Digital Object Identifier
- Title
-
A Novel Transferable Sparse Regression Method for Cross-Database Facial Expression RecognitionWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2021Year of publication
- Publication date
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2021-12-31Full publication date if available
- Authors
-
Wenjing Zhang, Peng Song, Wenming ZhengList of authors in order
- Landing page
-
https://doi.org/10.1587/transinf.2021edl8062Publisher landing page
- PDF URL
-
https://www.jstage.jst.go.jp/article/transinf/E105.D/1/E105.D_2021EDL8062/_pdfDirect link to full text PDF
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YesWhether a free full text is available
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diamondOpen access status per OpenAlex
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https://www.jstage.jst.go.jp/article/transinf/E105.D/1/E105.D_2021EDL8062/_pdfDirect OA link when available
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Computer science, Overfitting, Artificial intelligence, Pattern recognition (psychology), Pairwise comparison, Sparse approximation, Constraint (computer-aided design), Feature learning, Outlier, Machine learning, Mathematics, Artificial neural network, GeometryTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- References (count)
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16Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.transfer | 73, 82, 135 |
| abstract_inverted_index.validate | 122 |
| abstract_inverted_index.Moreover, | 92 |
| abstract_inverted_index.Secondly, | 75 |
| abstract_inverted_index.alleviate | 45 |
| abstract_inverted_index.conducted | 112 |
| abstract_inverted_index.influence | 47 |
| abstract_inverted_index.introduce | 94 |
| abstract_inverted_index.learning. | 74 |
| abstract_inverted_index.additional | 105 |
| abstract_inverted_index.constraint | 57, 97 |
| abstract_inverted_index.databases, | 118 |
| abstract_inverted_index.expression | 15, 117 |
| abstract_inverted_index.introduced | 68 |
| abstract_inverted_index.knowledge, | 83 |
| abstract_inverted_index.regression | 9, 25, 60 |
| abstract_inverted_index.structural | 106 |
| abstract_inverted_index.structure. | 91 |
| abstract_inverted_index.experiments | 110 |
| abstract_inverted_index.recognition | 16 |
| abstract_inverted_index.information. | 107 |
| abstract_inverted_index.overfitting, | 51 |
| abstract_inverted_index.transferable | 7 |
| abstract_inverted_index.cross-database | 13, 89 |
| abstract_inverted_index.regularization | 101 |
| abstract_inverted_index.representation | 34 |
| cited_by_percentile_year | |
| countries_distinct_count | 2 |
| institutions_distinct_count | 3 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/5 |
| sustainable_development_goals[0].score | 0.46000000834465027 |
| sustainable_development_goals[0].display_name | Gender equality |
| citation_normalized_percentile.value | 0.17447617 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |