Facial Feature Tracking via Evolutionary Multiobjective Optimization
Facial feature tracking for model–based coding has evolved over the past decades. Of particular interest is its application in very low bit rate coding in which optimization is used to analyze head and shoulder sequences. We present the results of a computational experiment in which we apply a combi...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Larson, Eric C. [verfasserIn] Yen, Gary G. [author] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2010 |
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| Schlagwörter: |
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| Umfang: |
Online-Ressource |
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| Reproduktion: |
IGI Global InfoSci Journals Archive 2000 - 2012 |
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| Übergeordnetes Werk: |
In: International journal of applied evolutionary computation - Hershey, Pa : IGI Global, 2010, 1(2010), 1, Seite 57-71 |
| Übergeordnetes Werk: |
volume:1 ; year:2010 ; number:1 ; pages:57-71 |
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| DOI / URN: |
10.4018/jaec.2010010104 |
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NLEJ244442991 |
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| 520 | |a Facial feature tracking for model–based coding has evolved over the past decades. Of particular interest is its application in very low bit rate coding in which optimization is used to analyze head and shoulder sequences. We present the results of a computational experiment in which we apply a combination of non-dominated sorting genetic algorithm and a deterministic search to find optimal facial animation parameters at many bandwidths simultaneously. As objective functions are concerned, peak signal-to-noise ratio is maximized while the total number of facial animation parameters is minimized. Particularly, the algorithm is tested for efficiency and reliability. The results show that the overall methodology works effectively, but that a better error assessment function is needed for future study | ||
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10.4018/jaec.2010010104 doi (DE-627)NLEJ244442991 (VZGNL)10.4018/jaec.2010010104 DE-627 ger DE-627 rakwb eng Larson, Eric C. verfasserin aut Facial Feature Tracking via Evolutionary Multiobjective Optimization 2010 Online-Ressource nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Facial feature tracking for model–based coding has evolved over the past decades. Of particular interest is its application in very low bit rate coding in which optimization is used to analyze head and shoulder sequences. We present the results of a computational experiment in which we apply a combination of non-dominated sorting genetic algorithm and a deterministic search to find optimal facial animation parameters at many bandwidths simultaneously. As objective functions are concerned, peak signal-to-noise ratio is maximized while the total number of facial animation parameters is minimized. Particularly, the algorithm is tested for efficiency and reliability. The results show that the overall methodology works effectively, but that a better error assessment function is needed for future study IGI Global InfoSci Journals Archive 2000 - 2012 Cyclic Optimization Genetic Algorithm Facial Feature Tracking Model-Based Coding Multiobjective Optimization NSGA-II Yen, Gary G. author aut In International journal of applied evolutionary computation Hershey, Pa : IGI Global, 2010 1(2010), 1, Seite 57-71 Online-Ressource (DE-627)NLEJ24441856X (DE-600)2696101-5 1942-3608 nnns volume:1 year:2010 number:1 pages:57-71 http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/jaec.2010010104 X:IGIG Verlag Deutschlandweit zugänglich http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/jaec.2010010104&buylink=true text/html Abstract Deutschlandweit zugänglich ZDB-1-GIS GBV_NL_ARTICLE AR 1 2010 1 57-71 |
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10.4018/jaec.2010010104 doi (DE-627)NLEJ244442991 (VZGNL)10.4018/jaec.2010010104 DE-627 ger DE-627 rakwb eng Larson, Eric C. verfasserin aut Facial Feature Tracking via Evolutionary Multiobjective Optimization 2010 Online-Ressource nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Facial feature tracking for model–based coding has evolved over the past decades. Of particular interest is its application in very low bit rate coding in which optimization is used to analyze head and shoulder sequences. We present the results of a computational experiment in which we apply a combination of non-dominated sorting genetic algorithm and a deterministic search to find optimal facial animation parameters at many bandwidths simultaneously. As objective functions are concerned, peak signal-to-noise ratio is maximized while the total number of facial animation parameters is minimized. Particularly, the algorithm is tested for efficiency and reliability. The results show that the overall methodology works effectively, but that a better error assessment function is needed for future study IGI Global InfoSci Journals Archive 2000 - 2012 Cyclic Optimization Genetic Algorithm Facial Feature Tracking Model-Based Coding Multiobjective Optimization NSGA-II Yen, Gary G. author aut In International journal of applied evolutionary computation Hershey, Pa : IGI Global, 2010 1(2010), 1, Seite 57-71 Online-Ressource (DE-627)NLEJ24441856X (DE-600)2696101-5 1942-3608 nnns volume:1 year:2010 number:1 pages:57-71 http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/jaec.2010010104 X:IGIG Verlag Deutschlandweit zugänglich http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/jaec.2010010104&buylink=true text/html Abstract Deutschlandweit zugänglich ZDB-1-GIS GBV_NL_ARTICLE AR 1 2010 1 57-71 |
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10.4018/jaec.2010010104 doi (DE-627)NLEJ244442991 (VZGNL)10.4018/jaec.2010010104 DE-627 ger DE-627 rakwb eng Larson, Eric C. verfasserin aut Facial Feature Tracking via Evolutionary Multiobjective Optimization 2010 Online-Ressource nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Facial feature tracking for model–based coding has evolved over the past decades. Of particular interest is its application in very low bit rate coding in which optimization is used to analyze head and shoulder sequences. We present the results of a computational experiment in which we apply a combination of non-dominated sorting genetic algorithm and a deterministic search to find optimal facial animation parameters at many bandwidths simultaneously. As objective functions are concerned, peak signal-to-noise ratio is maximized while the total number of facial animation parameters is minimized. Particularly, the algorithm is tested for efficiency and reliability. The results show that the overall methodology works effectively, but that a better error assessment function is needed for future study IGI Global InfoSci Journals Archive 2000 - 2012 Cyclic Optimization Genetic Algorithm Facial Feature Tracking Model-Based Coding Multiobjective Optimization NSGA-II Yen, Gary G. author aut In International journal of applied evolutionary computation Hershey, Pa : IGI Global, 2010 1(2010), 1, Seite 57-71 Online-Ressource (DE-627)NLEJ24441856X (DE-600)2696101-5 1942-3608 nnns volume:1 year:2010 number:1 pages:57-71 http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/jaec.2010010104 X:IGIG Verlag Deutschlandweit zugänglich http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/jaec.2010010104&buylink=true text/html Abstract Deutschlandweit zugänglich ZDB-1-GIS GBV_NL_ARTICLE AR 1 2010 1 57-71 |
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Facial feature tracking for model–based coding has evolved over the past decades. Of particular interest is its application in very low bit rate coding in which optimization is used to analyze head and shoulder sequences. We present the results of a computational experiment in which we apply a combination of non-dominated sorting genetic algorithm and a deterministic search to find optimal facial animation parameters at many bandwidths simultaneously. As objective functions are concerned, peak signal-to-noise ratio is maximized while the total number of facial animation parameters is minimized. Particularly, the algorithm is tested for efficiency and reliability. The results show that the overall methodology works effectively, but that a better error assessment function is needed for future study |
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Facial feature tracking for model–based coding has evolved over the past decades. Of particular interest is its application in very low bit rate coding in which optimization is used to analyze head and shoulder sequences. We present the results of a computational experiment in which we apply a combination of non-dominated sorting genetic algorithm and a deterministic search to find optimal facial animation parameters at many bandwidths simultaneously. As objective functions are concerned, peak signal-to-noise ratio is maximized while the total number of facial animation parameters is minimized. Particularly, the algorithm is tested for efficiency and reliability. The results show that the overall methodology works effectively, but that a better error assessment function is needed for future study |
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Facial feature tracking for model–based coding has evolved over the past decades. Of particular interest is its application in very low bit rate coding in which optimization is used to analyze head and shoulder sequences. We present the results of a computational experiment in which we apply a combination of non-dominated sorting genetic algorithm and a deterministic search to find optimal facial animation parameters at many bandwidths simultaneously. As objective functions are concerned, peak signal-to-noise ratio is maximized while the total number of facial animation parameters is minimized. Particularly, the algorithm is tested for efficiency and reliability. The results show that the overall methodology works effectively, but that a better error assessment function is needed for future study |
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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">NLEJ244442991</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20240202180045.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">150605s2010 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.4018/jaec.2010010104</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)NLEJ244442991</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(VZGNL)10.4018/jaec.2010010104</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">Larson, Eric C.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Facial Feature Tracking via Evolutionary Multiobjective Optimization</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2010</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zzz</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">z</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zu</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Facial feature tracking for model–based coding has evolved over the past decades. Of particular interest is its application in very low bit rate coding in which optimization is used to analyze head and shoulder sequences. We present the results of a computational experiment in which we apply a combination of non-dominated sorting genetic algorithm and a deterministic search to find optimal facial animation parameters at many bandwidths simultaneously. As objective functions are concerned, peak signal-to-noise ratio is maximized while the total number of facial animation parameters is minimized. Particularly, the algorithm is tested for efficiency and reliability. The results show that the overall methodology works effectively, but that a better error assessment function is needed for future study</subfield></datafield><datafield tag="533" ind1=" " ind2=" "><subfield code="f">IGI Global InfoSci Journals Archive 2000 - 2012</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Cyclic Optimization</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Genetic Algorithm</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Facial Feature Tracking</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Model-Based Coding</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Multiobjective Optimization</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">NSGA-II</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Yen, Gary G.</subfield><subfield code="e">author</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">In</subfield><subfield code="t">International journal of applied evolutionary computation</subfield><subfield code="d">Hershey, Pa : IGI Global, 2010</subfield><subfield code="g">1(2010), 1, Seite 57-71</subfield><subfield code="h">Online-Ressource</subfield><subfield code="w">(DE-627)NLEJ24441856X</subfield><subfield code="w">(DE-600)2696101-5</subfield><subfield code="x">1942-3608</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:1</subfield><subfield code="g">year:2010</subfield><subfield code="g">number:1</subfield><subfield code="g">pages:57-71</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/jaec.2010010104</subfield><subfield code="m">X:IGIG</subfield><subfield code="x">Verlag</subfield><subfield code="z">Deutschlandweit zugänglich</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/jaec.2010010104&buylink=true</subfield><subfield code="q">text/html</subfield><subfield code="y">Abstract</subfield><subfield code="z">Deutschlandweit zugänglich</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-1-GIS</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_NL_ARTICLE</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">1</subfield><subfield code="j">2010</subfield><subfield code="e">1</subfield><subfield code="h">57-71</subfield></datafield></record></collection>
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