Real time blink recognition from various head pose using single eye
Abstract A vision based human system interface has gained its significance in many areas like drowsy driving, Computer Vision Syndrome (CVS), face detection or recognition etc. The image processing method used in these applications for eye detection is Viola-Jones algorithm. In a natural communicati...
Ausführliche Beschreibung
Autor*in: |
John, Sofia Jennifer [verfasserIn] Sharmila, Sree T. [verfasserIn] |
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Format: |
E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2018 |
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Schlagwörter: |
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Übergeordnetes Werk: |
Enthalten in: Multimedia tools and applications - Dordrecht [u.a.] : Springer Science + Business Media B.V, 1995, 77(2018), 23 vom: 05. Juni, Seite 31331-31345 |
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Übergeordnetes Werk: |
volume:77 ; year:2018 ; number:23 ; day:05 ; month:06 ; pages:31331-31345 |
Links: |
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DOI / URN: |
10.1007/s11042-018-6113-3 |
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Katalog-ID: |
SPR016016289 |
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520 | |a Abstract A vision based human system interface has gained its significance in many areas like drowsy driving, Computer Vision Syndrome (CVS), face detection or recognition etc. The image processing method used in these applications for eye detection is Viola-Jones algorithm. In a natural communication environment, a human face tends to have different roll, yaw and pitch orientation angles. Thus, maintaining a straight focus with a camera is not always practically possible. Motivated by this challenge, experimental analysis is done to identify an eye blink on various head orientation angles. The proposed idea suggests using a single eye to detect the eye state (open or close) rather than both eyes, as blink detection is the rapid closure of both eyes simultaneously and a single eye can be progressively located for wider orientation angles. For analysis roll orientation angles are computed based on eye canthus line and yaw orientations angles are based on nose-line. Accepted experimental results from the customized dataset in different situations shows that the proposed work of using single eye outperforms both eyes with more accuracy and can be resolved for wider orientation angles. | ||
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10.1007/s11042-018-6113-3 doi (DE-627)SPR016016289 (DE-599)SPRs11042-018-6113-3-e (SPR)s11042-018-6113-3-e DE-627 ger DE-627 rakwb eng 070 004 ASE 54.87 bkl John, Sofia Jennifer verfasserin aut Real time blink recognition from various head pose using single eye 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract A vision based human system interface has gained its significance in many areas like drowsy driving, Computer Vision Syndrome (CVS), face detection or recognition etc. The image processing method used in these applications for eye detection is Viola-Jones algorithm. In a natural communication environment, a human face tends to have different roll, yaw and pitch orientation angles. Thus, maintaining a straight focus with a camera is not always practically possible. Motivated by this challenge, experimental analysis is done to identify an eye blink on various head orientation angles. The proposed idea suggests using a single eye to detect the eye state (open or close) rather than both eyes, as blink detection is the rapid closure of both eyes simultaneously and a single eye can be progressively located for wider orientation angles. For analysis roll orientation angles are computed based on eye canthus line and yaw orientations angles are based on nose-line. Accepted experimental results from the customized dataset in different situations shows that the proposed work of using single eye outperforms both eyes with more accuracy and can be resolved for wider orientation angles. Eye canthus (dpeaa)DE-He213 Roll and yaw orientations (dpeaa)DE-He213 Single eye detection (dpeaa)DE-He213 Viola-Jones algorithm (dpeaa)DE-He213 Sharmila, Sree T. verfasserin aut Enthalten in Multimedia tools and applications Dordrecht [u.a.] : Springer Science + Business Media B.V, 1995 77(2018), 23 vom: 05. Juni, Seite 31331-31345 (DE-627)27135030X (DE-600)1479928-5 1573-7721 nnns volume:77 year:2018 number:23 day:05 month:06 pages:31331-31345 https://dx.doi.org/10.1007/s11042-018-6113-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-BBI SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 54.87 ASE AR 77 2018 23 05 06 31331-31345 |
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10.1007/s11042-018-6113-3 doi (DE-627)SPR016016289 (DE-599)SPRs11042-018-6113-3-e (SPR)s11042-018-6113-3-e DE-627 ger DE-627 rakwb eng 070 004 ASE 54.87 bkl John, Sofia Jennifer verfasserin aut Real time blink recognition from various head pose using single eye 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract A vision based human system interface has gained its significance in many areas like drowsy driving, Computer Vision Syndrome (CVS), face detection or recognition etc. The image processing method used in these applications for eye detection is Viola-Jones algorithm. In a natural communication environment, a human face tends to have different roll, yaw and pitch orientation angles. Thus, maintaining a straight focus with a camera is not always practically possible. Motivated by this challenge, experimental analysis is done to identify an eye blink on various head orientation angles. The proposed idea suggests using a single eye to detect the eye state (open or close) rather than both eyes, as blink detection is the rapid closure of both eyes simultaneously and a single eye can be progressively located for wider orientation angles. For analysis roll orientation angles are computed based on eye canthus line and yaw orientations angles are based on nose-line. Accepted experimental results from the customized dataset in different situations shows that the proposed work of using single eye outperforms both eyes with more accuracy and can be resolved for wider orientation angles. Eye canthus (dpeaa)DE-He213 Roll and yaw orientations (dpeaa)DE-He213 Single eye detection (dpeaa)DE-He213 Viola-Jones algorithm (dpeaa)DE-He213 Sharmila, Sree T. verfasserin aut Enthalten in Multimedia tools and applications Dordrecht [u.a.] : Springer Science + Business Media B.V, 1995 77(2018), 23 vom: 05. Juni, Seite 31331-31345 (DE-627)27135030X (DE-600)1479928-5 1573-7721 nnns volume:77 year:2018 number:23 day:05 month:06 pages:31331-31345 https://dx.doi.org/10.1007/s11042-018-6113-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-BBI SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 54.87 ASE AR 77 2018 23 05 06 31331-31345 |
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10.1007/s11042-018-6113-3 doi (DE-627)SPR016016289 (DE-599)SPRs11042-018-6113-3-e (SPR)s11042-018-6113-3-e DE-627 ger DE-627 rakwb eng 070 004 ASE 54.87 bkl John, Sofia Jennifer verfasserin aut Real time blink recognition from various head pose using single eye 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract A vision based human system interface has gained its significance in many areas like drowsy driving, Computer Vision Syndrome (CVS), face detection or recognition etc. The image processing method used in these applications for eye detection is Viola-Jones algorithm. In a natural communication environment, a human face tends to have different roll, yaw and pitch orientation angles. Thus, maintaining a straight focus with a camera is not always practically possible. Motivated by this challenge, experimental analysis is done to identify an eye blink on various head orientation angles. The proposed idea suggests using a single eye to detect the eye state (open or close) rather than both eyes, as blink detection is the rapid closure of both eyes simultaneously and a single eye can be progressively located for wider orientation angles. For analysis roll orientation angles are computed based on eye canthus line and yaw orientations angles are based on nose-line. Accepted experimental results from the customized dataset in different situations shows that the proposed work of using single eye outperforms both eyes with more accuracy and can be resolved for wider orientation angles. Eye canthus (dpeaa)DE-He213 Roll and yaw orientations (dpeaa)DE-He213 Single eye detection (dpeaa)DE-He213 Viola-Jones algorithm (dpeaa)DE-He213 Sharmila, Sree T. verfasserin aut Enthalten in Multimedia tools and applications Dordrecht [u.a.] : Springer Science + Business Media B.V, 1995 77(2018), 23 vom: 05. Juni, Seite 31331-31345 (DE-627)27135030X (DE-600)1479928-5 1573-7721 nnns volume:77 year:2018 number:23 day:05 month:06 pages:31331-31345 https://dx.doi.org/10.1007/s11042-018-6113-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-BBI SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 54.87 ASE AR 77 2018 23 05 06 31331-31345 |
allfieldsGer |
10.1007/s11042-018-6113-3 doi (DE-627)SPR016016289 (DE-599)SPRs11042-018-6113-3-e (SPR)s11042-018-6113-3-e DE-627 ger DE-627 rakwb eng 070 004 ASE 54.87 bkl John, Sofia Jennifer verfasserin aut Real time blink recognition from various head pose using single eye 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract A vision based human system interface has gained its significance in many areas like drowsy driving, Computer Vision Syndrome (CVS), face detection or recognition etc. The image processing method used in these applications for eye detection is Viola-Jones algorithm. In a natural communication environment, a human face tends to have different roll, yaw and pitch orientation angles. Thus, maintaining a straight focus with a camera is not always practically possible. Motivated by this challenge, experimental analysis is done to identify an eye blink on various head orientation angles. The proposed idea suggests using a single eye to detect the eye state (open or close) rather than both eyes, as blink detection is the rapid closure of both eyes simultaneously and a single eye can be progressively located for wider orientation angles. For analysis roll orientation angles are computed based on eye canthus line and yaw orientations angles are based on nose-line. Accepted experimental results from the customized dataset in different situations shows that the proposed work of using single eye outperforms both eyes with more accuracy and can be resolved for wider orientation angles. Eye canthus (dpeaa)DE-He213 Roll and yaw orientations (dpeaa)DE-He213 Single eye detection (dpeaa)DE-He213 Viola-Jones algorithm (dpeaa)DE-He213 Sharmila, Sree T. verfasserin aut Enthalten in Multimedia tools and applications Dordrecht [u.a.] : Springer Science + Business Media B.V, 1995 77(2018), 23 vom: 05. Juni, Seite 31331-31345 (DE-627)27135030X (DE-600)1479928-5 1573-7721 nnns volume:77 year:2018 number:23 day:05 month:06 pages:31331-31345 https://dx.doi.org/10.1007/s11042-018-6113-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-BBI SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 54.87 ASE AR 77 2018 23 05 06 31331-31345 |
allfieldsSound |
10.1007/s11042-018-6113-3 doi (DE-627)SPR016016289 (DE-599)SPRs11042-018-6113-3-e (SPR)s11042-018-6113-3-e DE-627 ger DE-627 rakwb eng 070 004 ASE 54.87 bkl John, Sofia Jennifer verfasserin aut Real time blink recognition from various head pose using single eye 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract A vision based human system interface has gained its significance in many areas like drowsy driving, Computer Vision Syndrome (CVS), face detection or recognition etc. The image processing method used in these applications for eye detection is Viola-Jones algorithm. In a natural communication environment, a human face tends to have different roll, yaw and pitch orientation angles. Thus, maintaining a straight focus with a camera is not always practically possible. Motivated by this challenge, experimental analysis is done to identify an eye blink on various head orientation angles. The proposed idea suggests using a single eye to detect the eye state (open or close) rather than both eyes, as blink detection is the rapid closure of both eyes simultaneously and a single eye can be progressively located for wider orientation angles. For analysis roll orientation angles are computed based on eye canthus line and yaw orientations angles are based on nose-line. Accepted experimental results from the customized dataset in different situations shows that the proposed work of using single eye outperforms both eyes with more accuracy and can be resolved for wider orientation angles. Eye canthus (dpeaa)DE-He213 Roll and yaw orientations (dpeaa)DE-He213 Single eye detection (dpeaa)DE-He213 Viola-Jones algorithm (dpeaa)DE-He213 Sharmila, Sree T. verfasserin aut Enthalten in Multimedia tools and applications Dordrecht [u.a.] : Springer Science + Business Media B.V, 1995 77(2018), 23 vom: 05. Juni, Seite 31331-31345 (DE-627)27135030X (DE-600)1479928-5 1573-7721 nnns volume:77 year:2018 number:23 day:05 month:06 pages:31331-31345 https://dx.doi.org/10.1007/s11042-018-6113-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-BBI SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 54.87 ASE AR 77 2018 23 05 06 31331-31345 |
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|
author |
John, Sofia Jennifer |
spellingShingle |
John, Sofia Jennifer ddc 070 bkl 54.87 misc Eye canthus misc Roll and yaw orientations misc Single eye detection misc Viola-Jones algorithm Real time blink recognition from various head pose using single eye |
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070 004 ASE 54.87 bkl Real time blink recognition from various head pose using single eye Eye canthus (dpeaa)DE-He213 Roll and yaw orientations (dpeaa)DE-He213 Single eye detection (dpeaa)DE-He213 Viola-Jones algorithm (dpeaa)DE-He213 |
topic |
ddc 070 bkl 54.87 misc Eye canthus misc Roll and yaw orientations misc Single eye detection misc Viola-Jones algorithm |
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ddc 070 bkl 54.87 misc Eye canthus misc Roll and yaw orientations misc Single eye detection misc Viola-Jones algorithm |
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ddc 070 bkl 54.87 misc Eye canthus misc Roll and yaw orientations misc Single eye detection misc Viola-Jones algorithm |
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Real time blink recognition from various head pose using single eye |
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Real time blink recognition from various head pose using single eye |
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John, Sofia Jennifer |
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real time blink recognition from various head pose using single eye |
title_auth |
Real time blink recognition from various head pose using single eye |
abstract |
Abstract A vision based human system interface has gained its significance in many areas like drowsy driving, Computer Vision Syndrome (CVS), face detection or recognition etc. The image processing method used in these applications for eye detection is Viola-Jones algorithm. In a natural communication environment, a human face tends to have different roll, yaw and pitch orientation angles. Thus, maintaining a straight focus with a camera is not always practically possible. Motivated by this challenge, experimental analysis is done to identify an eye blink on various head orientation angles. The proposed idea suggests using a single eye to detect the eye state (open or close) rather than both eyes, as blink detection is the rapid closure of both eyes simultaneously and a single eye can be progressively located for wider orientation angles. For analysis roll orientation angles are computed based on eye canthus line and yaw orientations angles are based on nose-line. Accepted experimental results from the customized dataset in different situations shows that the proposed work of using single eye outperforms both eyes with more accuracy and can be resolved for wider orientation angles. |
abstractGer |
Abstract A vision based human system interface has gained its significance in many areas like drowsy driving, Computer Vision Syndrome (CVS), face detection or recognition etc. The image processing method used in these applications for eye detection is Viola-Jones algorithm. In a natural communication environment, a human face tends to have different roll, yaw and pitch orientation angles. Thus, maintaining a straight focus with a camera is not always practically possible. Motivated by this challenge, experimental analysis is done to identify an eye blink on various head orientation angles. The proposed idea suggests using a single eye to detect the eye state (open or close) rather than both eyes, as blink detection is the rapid closure of both eyes simultaneously and a single eye can be progressively located for wider orientation angles. For analysis roll orientation angles are computed based on eye canthus line and yaw orientations angles are based on nose-line. Accepted experimental results from the customized dataset in different situations shows that the proposed work of using single eye outperforms both eyes with more accuracy and can be resolved for wider orientation angles. |
abstract_unstemmed |
Abstract A vision based human system interface has gained its significance in many areas like drowsy driving, Computer Vision Syndrome (CVS), face detection or recognition etc. The image processing method used in these applications for eye detection is Viola-Jones algorithm. In a natural communication environment, a human face tends to have different roll, yaw and pitch orientation angles. Thus, maintaining a straight focus with a camera is not always practically possible. Motivated by this challenge, experimental analysis is done to identify an eye blink on various head orientation angles. The proposed idea suggests using a single eye to detect the eye state (open or close) rather than both eyes, as blink detection is the rapid closure of both eyes simultaneously and a single eye can be progressively located for wider orientation angles. For analysis roll orientation angles are computed based on eye canthus line and yaw orientations angles are based on nose-line. Accepted experimental results from the customized dataset in different situations shows that the proposed work of using single eye outperforms both eyes with more accuracy and can be resolved for wider orientation angles. |
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container_issue |
23 |
title_short |
Real time blink recognition from various head pose using single eye |
url |
https://dx.doi.org/10.1007/s11042-018-6113-3 |
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author2 |
Sharmila, Sree T. |
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Sharmila, Sree T. |
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doi_str |
10.1007/s11042-018-6113-3 |
up_date |
2024-07-03T20:12:11.830Z |
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score |
7.3974285 |