Advanced driver monitoring for assistance system (ADMAS)
Abstract The present study aimed to introduce an approach to implement facial analysis on monitoring driver emotional status in real time. For this purpose, an experimental setup had been performed based on commercial technologies. Such experimental protocol includes the main variables involved in d...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Izquierdo-Reyes, Javier [verfasserIn] Ramirez-Mendoza, Ricardo A. [verfasserIn] Bustamante-Bello, Martin R. [verfasserIn] Navarro-Tuch, Sergio [verfasserIn] Avila-Vazquez, Roberto [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2016 |
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| Schlagwörter: |
Advanced driver assistance systems |
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| Übergeordnetes Werk: |
Enthalten in: International journal on interactive design and manufacturing - Paris : Springer, 2007, 12(2016), 1 vom: 17. Sept., Seite 187-197 |
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| Übergeordnetes Werk: |
volume:12 ; year:2016 ; number:1 ; day:17 ; month:09 ; pages:187-197 |
| Links: |
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| DOI / URN: |
10.1007/s12008-016-0349-9 |
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| Katalog-ID: |
SPR024077607 |
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| 520 | |a Abstract The present study aimed to introduce an approach to implement facial analysis on monitoring driver emotional status in real time. For this purpose, an experimental setup had been performed based on commercial technologies. Such experimental protocol includes the main variables involved in driving and how those variables influence in the driver performance. The goal of the experimental design was to detect which emotions of the driver s face are present during driving and how those emotions can be changed in presence of stimuli from a passive advanced driver for assistance systems (ADAS). Finally, the idea is to investigate if the driver performance changes when some external stimuli are applied as hazards are reported to the driver. The experimental results suggest that the ADAS is not sufficient to enhance the driver’s performance. As a result, the authors propose a new framework for driver assistance systems based on driver state, especially emotions: advanced driver monitoring for assistance systems (ADMAS), refer to Fig. 1. With ADMAS implementation security and intelligence can be provided to a car and thus help to reduce traffic accidents. | ||
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| 650 | 4 | |a Advanced driver assistance systems |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Advance driver monitoring for assistance systems |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Emotions recognition |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Ramirez-Mendoza, Ricardo A. |e verfasserin |4 aut | |
| 700 | 1 | |a Bustamante-Bello, Martin R. |e verfasserin |4 aut | |
| 700 | 1 | |a Navarro-Tuch, Sergio |e verfasserin |4 aut | |
| 700 | 1 | |a Avila-Vazquez, Roberto |e verfasserin |4 aut | |
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10.1007/s12008-016-0349-9 doi (DE-627)SPR024077607 (SPR)s12008-016-0349-9-e DE-627 ger DE-627 rakwb eng 690 ASE Izquierdo-Reyes, Javier verfasserin aut Advanced driver monitoring for assistance system (ADMAS) 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The present study aimed to introduce an approach to implement facial analysis on monitoring driver emotional status in real time. For this purpose, an experimental setup had been performed based on commercial technologies. Such experimental protocol includes the main variables involved in driving and how those variables influence in the driver performance. The goal of the experimental design was to detect which emotions of the driver s face are present during driving and how those emotions can be changed in presence of stimuli from a passive advanced driver for assistance systems (ADAS). Finally, the idea is to investigate if the driver performance changes when some external stimuli are applied as hazards are reported to the driver. The experimental results suggest that the ADAS is not sufficient to enhance the driver’s performance. As a result, the authors propose a new framework for driver assistance systems based on driver state, especially emotions: advanced driver monitoring for assistance systems (ADMAS), refer to Fig. 1. With ADMAS implementation security and intelligence can be provided to a car and thus help to reduce traffic accidents. Driver monitoring (dpeaa)DE-He213 Advanced driver assistance systems (dpeaa)DE-He213 Advance driver monitoring for assistance systems (dpeaa)DE-He213 Emotions recognition (dpeaa)DE-He213 Ramirez-Mendoza, Ricardo A. verfasserin aut Bustamante-Bello, Martin R. verfasserin aut Navarro-Tuch, Sergio verfasserin aut Avila-Vazquez, Roberto verfasserin aut Enthalten in International journal on interactive design and manufacturing Paris : Springer, 2007 12(2016), 1 vom: 17. Sept., Seite 187-197 (DE-627)546503195 (DE-600)2390733-2 1955-2505 nnns volume:12 year:2016 number:1 day:17 month:09 pages:187-197 https://dx.doi.org/10.1007/s12008-016-0349-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 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_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 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 AR 12 2016 1 17 09 187-197 |
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10.1007/s12008-016-0349-9 doi (DE-627)SPR024077607 (SPR)s12008-016-0349-9-e DE-627 ger DE-627 rakwb eng 690 ASE Izquierdo-Reyes, Javier verfasserin aut Advanced driver monitoring for assistance system (ADMAS) 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The present study aimed to introduce an approach to implement facial analysis on monitoring driver emotional status in real time. For this purpose, an experimental setup had been performed based on commercial technologies. Such experimental protocol includes the main variables involved in driving and how those variables influence in the driver performance. The goal of the experimental design was to detect which emotions of the driver s face are present during driving and how those emotions can be changed in presence of stimuli from a passive advanced driver for assistance systems (ADAS). Finally, the idea is to investigate if the driver performance changes when some external stimuli are applied as hazards are reported to the driver. The experimental results suggest that the ADAS is not sufficient to enhance the driver’s performance. As a result, the authors propose a new framework for driver assistance systems based on driver state, especially emotions: advanced driver monitoring for assistance systems (ADMAS), refer to Fig. 1. With ADMAS implementation security and intelligence can be provided to a car and thus help to reduce traffic accidents. Driver monitoring (dpeaa)DE-He213 Advanced driver assistance systems (dpeaa)DE-He213 Advance driver monitoring for assistance systems (dpeaa)DE-He213 Emotions recognition (dpeaa)DE-He213 Ramirez-Mendoza, Ricardo A. verfasserin aut Bustamante-Bello, Martin R. verfasserin aut Navarro-Tuch, Sergio verfasserin aut Avila-Vazquez, Roberto verfasserin aut Enthalten in International journal on interactive design and manufacturing Paris : Springer, 2007 12(2016), 1 vom: 17. Sept., Seite 187-197 (DE-627)546503195 (DE-600)2390733-2 1955-2505 nnns volume:12 year:2016 number:1 day:17 month:09 pages:187-197 https://dx.doi.org/10.1007/s12008-016-0349-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 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_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 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 AR 12 2016 1 17 09 187-197 |
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10.1007/s12008-016-0349-9 doi (DE-627)SPR024077607 (SPR)s12008-016-0349-9-e DE-627 ger DE-627 rakwb eng 690 ASE Izquierdo-Reyes, Javier verfasserin aut Advanced driver monitoring for assistance system (ADMAS) 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The present study aimed to introduce an approach to implement facial analysis on monitoring driver emotional status in real time. For this purpose, an experimental setup had been performed based on commercial technologies. Such experimental protocol includes the main variables involved in driving and how those variables influence in the driver performance. The goal of the experimental design was to detect which emotions of the driver s face are present during driving and how those emotions can be changed in presence of stimuli from a passive advanced driver for assistance systems (ADAS). Finally, the idea is to investigate if the driver performance changes when some external stimuli are applied as hazards are reported to the driver. The experimental results suggest that the ADAS is not sufficient to enhance the driver’s performance. As a result, the authors propose a new framework for driver assistance systems based on driver state, especially emotions: advanced driver monitoring for assistance systems (ADMAS), refer to Fig. 1. With ADMAS implementation security and intelligence can be provided to a car and thus help to reduce traffic accidents. Driver monitoring (dpeaa)DE-He213 Advanced driver assistance systems (dpeaa)DE-He213 Advance driver monitoring for assistance systems (dpeaa)DE-He213 Emotions recognition (dpeaa)DE-He213 Ramirez-Mendoza, Ricardo A. verfasserin aut Bustamante-Bello, Martin R. verfasserin aut Navarro-Tuch, Sergio verfasserin aut Avila-Vazquez, Roberto verfasserin aut Enthalten in International journal on interactive design and manufacturing Paris : Springer, 2007 12(2016), 1 vom: 17. Sept., Seite 187-197 (DE-627)546503195 (DE-600)2390733-2 1955-2505 nnns volume:12 year:2016 number:1 day:17 month:09 pages:187-197 https://dx.doi.org/10.1007/s12008-016-0349-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 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_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 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 AR 12 2016 1 17 09 187-197 |
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10.1007/s12008-016-0349-9 doi (DE-627)SPR024077607 (SPR)s12008-016-0349-9-e DE-627 ger DE-627 rakwb eng 690 ASE Izquierdo-Reyes, Javier verfasserin aut Advanced driver monitoring for assistance system (ADMAS) 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The present study aimed to introduce an approach to implement facial analysis on monitoring driver emotional status in real time. For this purpose, an experimental setup had been performed based on commercial technologies. Such experimental protocol includes the main variables involved in driving and how those variables influence in the driver performance. The goal of the experimental design was to detect which emotions of the driver s face are present during driving and how those emotions can be changed in presence of stimuli from a passive advanced driver for assistance systems (ADAS). Finally, the idea is to investigate if the driver performance changes when some external stimuli are applied as hazards are reported to the driver. The experimental results suggest that the ADAS is not sufficient to enhance the driver’s performance. As a result, the authors propose a new framework for driver assistance systems based on driver state, especially emotions: advanced driver monitoring for assistance systems (ADMAS), refer to Fig. 1. With ADMAS implementation security and intelligence can be provided to a car and thus help to reduce traffic accidents. Driver monitoring (dpeaa)DE-He213 Advanced driver assistance systems (dpeaa)DE-He213 Advance driver monitoring for assistance systems (dpeaa)DE-He213 Emotions recognition (dpeaa)DE-He213 Ramirez-Mendoza, Ricardo A. verfasserin aut Bustamante-Bello, Martin R. verfasserin aut Navarro-Tuch, Sergio verfasserin aut Avila-Vazquez, Roberto verfasserin aut Enthalten in International journal on interactive design and manufacturing Paris : Springer, 2007 12(2016), 1 vom: 17. Sept., Seite 187-197 (DE-627)546503195 (DE-600)2390733-2 1955-2505 nnns volume:12 year:2016 number:1 day:17 month:09 pages:187-197 https://dx.doi.org/10.1007/s12008-016-0349-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 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_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 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 AR 12 2016 1 17 09 187-197 |
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10.1007/s12008-016-0349-9 doi (DE-627)SPR024077607 (SPR)s12008-016-0349-9-e DE-627 ger DE-627 rakwb eng 690 ASE Izquierdo-Reyes, Javier verfasserin aut Advanced driver monitoring for assistance system (ADMAS) 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The present study aimed to introduce an approach to implement facial analysis on monitoring driver emotional status in real time. For this purpose, an experimental setup had been performed based on commercial technologies. Such experimental protocol includes the main variables involved in driving and how those variables influence in the driver performance. The goal of the experimental design was to detect which emotions of the driver s face are present during driving and how those emotions can be changed in presence of stimuli from a passive advanced driver for assistance systems (ADAS). Finally, the idea is to investigate if the driver performance changes when some external stimuli are applied as hazards are reported to the driver. The experimental results suggest that the ADAS is not sufficient to enhance the driver’s performance. As a result, the authors propose a new framework for driver assistance systems based on driver state, especially emotions: advanced driver monitoring for assistance systems (ADMAS), refer to Fig. 1. With ADMAS implementation security and intelligence can be provided to a car and thus help to reduce traffic accidents. Driver monitoring (dpeaa)DE-He213 Advanced driver assistance systems (dpeaa)DE-He213 Advance driver monitoring for assistance systems (dpeaa)DE-He213 Emotions recognition (dpeaa)DE-He213 Ramirez-Mendoza, Ricardo A. verfasserin aut Bustamante-Bello, Martin R. verfasserin aut Navarro-Tuch, Sergio verfasserin aut Avila-Vazquez, Roberto verfasserin aut Enthalten in International journal on interactive design and manufacturing Paris : Springer, 2007 12(2016), 1 vom: 17. Sept., Seite 187-197 (DE-627)546503195 (DE-600)2390733-2 1955-2505 nnns volume:12 year:2016 number:1 day:17 month:09 pages:187-197 https://dx.doi.org/10.1007/s12008-016-0349-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 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_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 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 AR 12 2016 1 17 09 187-197 |
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Enthalten in International journal on interactive design and manufacturing 12(2016), 1 vom: 17. Sept., Seite 187-197 volume:12 year:2016 number:1 day:17 month:09 pages:187-197 |
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Driver monitoring Advanced driver assistance systems Advance driver monitoring for assistance systems Emotions recognition |
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International journal on interactive design and manufacturing |
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Izquierdo-Reyes, Javier @@aut@@ Ramirez-Mendoza, Ricardo A. @@aut@@ Bustamante-Bello, Martin R. @@aut@@ Navarro-Tuch, Sergio @@aut@@ Avila-Vazquez, Roberto @@aut@@ |
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2016-09-17T00:00:00Z |
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|
| author |
Izquierdo-Reyes, Javier |
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Izquierdo-Reyes, Javier ddc 690 misc Driver monitoring misc Advanced driver assistance systems misc Advance driver monitoring for assistance systems misc Emotions recognition Advanced driver monitoring for assistance system (ADMAS) |
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Izquierdo-Reyes, Javier |
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690 ASE Advanced driver monitoring for assistance system (ADMAS) Driver monitoring (dpeaa)DE-He213 Advanced driver assistance systems (dpeaa)DE-He213 Advance driver monitoring for assistance systems (dpeaa)DE-He213 Emotions recognition (dpeaa)DE-He213 |
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ddc 690 misc Driver monitoring misc Advanced driver assistance systems misc Advance driver monitoring for assistance systems misc Emotions recognition |
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ddc 690 misc Driver monitoring misc Advanced driver assistance systems misc Advance driver monitoring for assistance systems misc Emotions recognition |
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ddc 690 misc Driver monitoring misc Advanced driver assistance systems misc Advance driver monitoring for assistance systems misc Emotions recognition |
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International journal on interactive design and manufacturing |
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Advanced driver monitoring for assistance system (ADMAS) |
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Izquierdo-Reyes, Javier |
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International journal on interactive design and manufacturing |
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Izquierdo-Reyes, Javier Ramirez-Mendoza, Ricardo A. Bustamante-Bello, Martin R. Navarro-Tuch, Sergio Avila-Vazquez, Roberto |
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Izquierdo-Reyes, Javier |
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advanced driver monitoring for assistance system (admas) |
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Advanced driver monitoring for assistance system (ADMAS) |
| abstract |
Abstract The present study aimed to introduce an approach to implement facial analysis on monitoring driver emotional status in real time. For this purpose, an experimental setup had been performed based on commercial technologies. Such experimental protocol includes the main variables involved in driving and how those variables influence in the driver performance. The goal of the experimental design was to detect which emotions of the driver s face are present during driving and how those emotions can be changed in presence of stimuli from a passive advanced driver for assistance systems (ADAS). Finally, the idea is to investigate if the driver performance changes when some external stimuli are applied as hazards are reported to the driver. The experimental results suggest that the ADAS is not sufficient to enhance the driver’s performance. As a result, the authors propose a new framework for driver assistance systems based on driver state, especially emotions: advanced driver monitoring for assistance systems (ADMAS), refer to Fig. 1. With ADMAS implementation security and intelligence can be provided to a car and thus help to reduce traffic accidents. |
| abstractGer |
Abstract The present study aimed to introduce an approach to implement facial analysis on monitoring driver emotional status in real time. For this purpose, an experimental setup had been performed based on commercial technologies. Such experimental protocol includes the main variables involved in driving and how those variables influence in the driver performance. The goal of the experimental design was to detect which emotions of the driver s face are present during driving and how those emotions can be changed in presence of stimuli from a passive advanced driver for assistance systems (ADAS). Finally, the idea is to investigate if the driver performance changes when some external stimuli are applied as hazards are reported to the driver. The experimental results suggest that the ADAS is not sufficient to enhance the driver’s performance. As a result, the authors propose a new framework for driver assistance systems based on driver state, especially emotions: advanced driver monitoring for assistance systems (ADMAS), refer to Fig. 1. With ADMAS implementation security and intelligence can be provided to a car and thus help to reduce traffic accidents. |
| abstract_unstemmed |
Abstract The present study aimed to introduce an approach to implement facial analysis on monitoring driver emotional status in real time. For this purpose, an experimental setup had been performed based on commercial technologies. Such experimental protocol includes the main variables involved in driving and how those variables influence in the driver performance. The goal of the experimental design was to detect which emotions of the driver s face are present during driving and how those emotions can be changed in presence of stimuli from a passive advanced driver for assistance systems (ADAS). Finally, the idea is to investigate if the driver performance changes when some external stimuli are applied as hazards are reported to the driver. The experimental results suggest that the ADAS is not sufficient to enhance the driver’s performance. As a result, the authors propose a new framework for driver assistance systems based on driver state, especially emotions: advanced driver monitoring for assistance systems (ADMAS), refer to Fig. 1. With ADMAS implementation security and intelligence can be provided to a car and thus help to reduce traffic accidents. |
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| title_short |
Advanced driver monitoring for assistance system (ADMAS) |
| url |
https://dx.doi.org/10.1007/s12008-016-0349-9 |
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true |
| author2 |
Ramirez-Mendoza, Ricardo A. Bustamante-Bello, Martin R. Navarro-Tuch, Sergio Avila-Vazquez, Roberto |
| author2Str |
Ramirez-Mendoza, Ricardo A. Bustamante-Bello, Martin R. Navarro-Tuch, Sergio Avila-Vazquez, Roberto |
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| doi_str |
10.1007/s12008-016-0349-9 |
| up_date |
2024-07-03T23:20:21.751Z |
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|
| score |
7.401597 |