Robust eye centers localization with zero-crossing encoded image projections
Abstract This paper proposes a new framework for the eye centers localization by the joint use of encoding of normalized image projections and a multi-layer perceptron (MLP) classifier. The encoding is novel and it consists in identifying the zero-crossings and extracting the relevant parameters fro...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Florea, Laura [verfasserIn] Florea, Corneliu [verfasserIn] Vertan, Constantin [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2015 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Pattern Analysis & Applications - Springer-Verlag, 1999, 20(2015), 1 vom: 09. Mai, Seite 127-143 |
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| Übergeordnetes Werk: |
volume:20 ; year:2015 ; number:1 ; day:09 ; month:05 ; pages:127-143 |
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| DOI / URN: |
10.1007/s10044-015-0479-x |
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| 520 | |a Abstract This paper proposes a new framework for the eye centers localization by the joint use of encoding of normalized image projections and a multi-layer perceptron (MLP) classifier. The encoding is novel and it consists in identifying the zero-crossings and extracting the relevant parameters from the resulting modes. The compressed normalized projections produce feature descriptors that are inputs to a properly trained MLP, for discriminating among various categories of image regions. The proposed framework forms a fast and reliable system for the eye centers localization, especially in the context of face expression analysis in unconstrained environments. We successfully test the proposed method on a wide variety of databases including BioID, Cohn–Kanade, Extended Yale B and Labeled faces in the wild databases. | ||
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10.1007/s10044-015-0479-x doi (DE-627)SPR008216053 (SPR)s10044-015-0479-x-e DE-627 ger DE-627 rakwb eng Florea, Laura verfasserin aut Robust eye centers localization with zero-crossing encoded image projections 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This paper proposes a new framework for the eye centers localization by the joint use of encoding of normalized image projections and a multi-layer perceptron (MLP) classifier. The encoding is novel and it consists in identifying the zero-crossings and extracting the relevant parameters from the resulting modes. The compressed normalized projections produce feature descriptors that are inputs to a properly trained MLP, for discriminating among various categories of image regions. The proposed framework forms a fast and reliable system for the eye centers localization, especially in the context of face expression analysis in unconstrained environments. We successfully test the proposed method on a wide variety of databases including BioID, Cohn–Kanade, Extended Yale B and Labeled faces in the wild databases. Eye localization (dpeaa)DE-He213 Image projections (dpeaa)DE-He213 Zero-crossing encoding (dpeaa)DE-He213 Real time (dpeaa)DE-He213 Florea, Corneliu verfasserin aut Vertan, Constantin verfasserin aut Enthalten in Pattern Analysis & Applications Springer-Verlag, 1999 20(2015), 1 vom: 09. Mai, Seite 127-143 (DE-627)SPR008209189 nnns volume:20 year:2015 number:1 day:09 month:05 pages:127-143 https://dx.doi.org/10.1007/s10044-015-0479-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER AR 20 2015 1 09 05 127-143 |
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10.1007/s10044-015-0479-x doi (DE-627)SPR008216053 (SPR)s10044-015-0479-x-e DE-627 ger DE-627 rakwb eng Florea, Laura verfasserin aut Robust eye centers localization with zero-crossing encoded image projections 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This paper proposes a new framework for the eye centers localization by the joint use of encoding of normalized image projections and a multi-layer perceptron (MLP) classifier. The encoding is novel and it consists in identifying the zero-crossings and extracting the relevant parameters from the resulting modes. The compressed normalized projections produce feature descriptors that are inputs to a properly trained MLP, for discriminating among various categories of image regions. The proposed framework forms a fast and reliable system for the eye centers localization, especially in the context of face expression analysis in unconstrained environments. We successfully test the proposed method on a wide variety of databases including BioID, Cohn–Kanade, Extended Yale B and Labeled faces in the wild databases. Eye localization (dpeaa)DE-He213 Image projections (dpeaa)DE-He213 Zero-crossing encoding (dpeaa)DE-He213 Real time (dpeaa)DE-He213 Florea, Corneliu verfasserin aut Vertan, Constantin verfasserin aut Enthalten in Pattern Analysis & Applications Springer-Verlag, 1999 20(2015), 1 vom: 09. Mai, Seite 127-143 (DE-627)SPR008209189 nnns volume:20 year:2015 number:1 day:09 month:05 pages:127-143 https://dx.doi.org/10.1007/s10044-015-0479-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER AR 20 2015 1 09 05 127-143 |
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10.1007/s10044-015-0479-x doi (DE-627)SPR008216053 (SPR)s10044-015-0479-x-e DE-627 ger DE-627 rakwb eng Florea, Laura verfasserin aut Robust eye centers localization with zero-crossing encoded image projections 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This paper proposes a new framework for the eye centers localization by the joint use of encoding of normalized image projections and a multi-layer perceptron (MLP) classifier. The encoding is novel and it consists in identifying the zero-crossings and extracting the relevant parameters from the resulting modes. The compressed normalized projections produce feature descriptors that are inputs to a properly trained MLP, for discriminating among various categories of image regions. The proposed framework forms a fast and reliable system for the eye centers localization, especially in the context of face expression analysis in unconstrained environments. We successfully test the proposed method on a wide variety of databases including BioID, Cohn–Kanade, Extended Yale B and Labeled faces in the wild databases. Eye localization (dpeaa)DE-He213 Image projections (dpeaa)DE-He213 Zero-crossing encoding (dpeaa)DE-He213 Real time (dpeaa)DE-He213 Florea, Corneliu verfasserin aut Vertan, Constantin verfasserin aut Enthalten in Pattern Analysis & Applications Springer-Verlag, 1999 20(2015), 1 vom: 09. Mai, Seite 127-143 (DE-627)SPR008209189 nnns volume:20 year:2015 number:1 day:09 month:05 pages:127-143 https://dx.doi.org/10.1007/s10044-015-0479-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER AR 20 2015 1 09 05 127-143 |
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10.1007/s10044-015-0479-x doi (DE-627)SPR008216053 (SPR)s10044-015-0479-x-e DE-627 ger DE-627 rakwb eng Florea, Laura verfasserin aut Robust eye centers localization with zero-crossing encoded image projections 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This paper proposes a new framework for the eye centers localization by the joint use of encoding of normalized image projections and a multi-layer perceptron (MLP) classifier. The encoding is novel and it consists in identifying the zero-crossings and extracting the relevant parameters from the resulting modes. The compressed normalized projections produce feature descriptors that are inputs to a properly trained MLP, for discriminating among various categories of image regions. The proposed framework forms a fast and reliable system for the eye centers localization, especially in the context of face expression analysis in unconstrained environments. We successfully test the proposed method on a wide variety of databases including BioID, Cohn–Kanade, Extended Yale B and Labeled faces in the wild databases. Eye localization (dpeaa)DE-He213 Image projections (dpeaa)DE-He213 Zero-crossing encoding (dpeaa)DE-He213 Real time (dpeaa)DE-He213 Florea, Corneliu verfasserin aut Vertan, Constantin verfasserin aut Enthalten in Pattern Analysis & Applications Springer-Verlag, 1999 20(2015), 1 vom: 09. Mai, Seite 127-143 (DE-627)SPR008209189 nnns volume:20 year:2015 number:1 day:09 month:05 pages:127-143 https://dx.doi.org/10.1007/s10044-015-0479-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER AR 20 2015 1 09 05 127-143 |
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Abstract This paper proposes a new framework for the eye centers localization by the joint use of encoding of normalized image projections and a multi-layer perceptron (MLP) classifier. The encoding is novel and it consists in identifying the zero-crossings and extracting the relevant parameters from the resulting modes. The compressed normalized projections produce feature descriptors that are inputs to a properly trained MLP, for discriminating among various categories of image regions. The proposed framework forms a fast and reliable system for the eye centers localization, especially in the context of face expression analysis in unconstrained environments. We successfully test the proposed method on a wide variety of databases including BioID, Cohn–Kanade, Extended Yale B and Labeled faces in the wild databases. |
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Abstract This paper proposes a new framework for the eye centers localization by the joint use of encoding of normalized image projections and a multi-layer perceptron (MLP) classifier. The encoding is novel and it consists in identifying the zero-crossings and extracting the relevant parameters from the resulting modes. The compressed normalized projections produce feature descriptors that are inputs to a properly trained MLP, for discriminating among various categories of image regions. The proposed framework forms a fast and reliable system for the eye centers localization, especially in the context of face expression analysis in unconstrained environments. We successfully test the proposed method on a wide variety of databases including BioID, Cohn–Kanade, Extended Yale B and Labeled faces in the wild databases. |
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Abstract This paper proposes a new framework for the eye centers localization by the joint use of encoding of normalized image projections and a multi-layer perceptron (MLP) classifier. The encoding is novel and it consists in identifying the zero-crossings and extracting the relevant parameters from the resulting modes. The compressed normalized projections produce feature descriptors that are inputs to a properly trained MLP, for discriminating among various categories of image regions. The proposed framework forms a fast and reliable system for the eye centers localization, especially in the context of face expression analysis in unconstrained environments. We successfully test the proposed method on a wide variety of databases including BioID, Cohn–Kanade, Extended Yale B and Labeled faces in the wild databases. |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">SPR008216053</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20201124023807.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">201005s2015 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s10044-015-0479-x</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR008216053</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s10044-015-0479-x-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Florea, Laura</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Robust eye centers localization with zero-crossing encoded image projections</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2015</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract This paper proposes a new framework for the eye centers localization by the joint use of encoding of normalized image projections and a multi-layer perceptron (MLP) classifier. The encoding is novel and it consists in identifying the zero-crossings and extracting the relevant parameters from the resulting modes. The compressed normalized projections produce feature descriptors that are inputs to a properly trained MLP, for discriminating among various categories of image regions. The proposed framework forms a fast and reliable system for the eye centers localization, especially in the context of face expression analysis in unconstrained environments. We successfully test the proposed method on a wide variety of databases including BioID, Cohn–Kanade, Extended Yale B and Labeled faces in the wild databases.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Eye localization</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Image projections</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Zero-crossing encoding</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Real time</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Florea, Corneliu</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Vertan, Constantin</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Pattern Analysis & Applications</subfield><subfield code="d">Springer-Verlag, 1999</subfield><subfield code="g">20(2015), 1 vom: 09. Mai, Seite 127-143</subfield><subfield code="w">(DE-627)SPR008209189</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:20</subfield><subfield code="g">year:2015</subfield><subfield code="g">number:1</subfield><subfield code="g">day:09</subfield><subfield code="g">month:05</subfield><subfield code="g">pages:127-143</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://dx.doi.org/10.1007/s10044-015-0479-x</subfield><subfield code="z">lizenzpflichtig</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_SPRINGER</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">20</subfield><subfield code="j">2015</subfield><subfield code="e">1</subfield><subfield code="b">09</subfield><subfield code="c">05</subfield><subfield code="h">127-143</subfield></datafield></record></collection>
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