Beyond Cognitive Signals

Abstract Although audio-visual human systems have several well-known limitations, artificial sensors can measure information beyond our limits. What would happen if we were able to overcome our limitations? Would we be able to obtain a better knowledge of our environment? Or the information beyond o...
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Autor*in:	Espinosa-Duró, Virginia [verfasserIn] Faundez-Zanuy, Marcos Mekyska, Jiří

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2010

Schlagwörter:	Image analysis Information theory Face Thermal image Visible image Near-infrared image

Anmerkung:	© Springer Science+Business Media, LLC 2010

Übergeordnetes Werk:	Enthalten in: Cognitive Computation - New York, NY : Springer, 2009, 3(2010), 2 vom: 20. März, Seite 374-381
Übergeordnetes Werk:	volume:3 ; year:2010 ; number:2 ; day:20 ; month:03 ; pages:374-381

Links:	Volltext

DOI / URN:	10.1007/s12559-010-9035-6

Katalog-ID:	SPR026477084

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520			\|a Abstract Although audio-visual human systems have several well-known limitations, artificial sensors can measure information beyond our limits. What would happen if we were able to overcome our limitations? Would we be able to obtain a better knowledge of our environment? Or the information beyond our limits is redundant? In this paper, we compare infrared, thermal and visible images from an information theory point of view. We have acquired a small database and compared several measurements over these images. While infrasounds and ultrasounds are not directly applicable, for instance, to speaker recognition due to the impossibility of human beings generating sounds in these frequencies, this is not the case with image signals beyond the visible spectrum for face recognition. We have observed that visible, near-infrared and thermal images contain a small amount of redundancy (less than 1,55 bits).
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700	1		\|a Mekyska, Jiří \|4 aut
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912			\|a GBV_ILN_2026
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allfields	10.1007/s12559-010-9035-6 doi (DE-627)SPR026477084 (SPR)s12559-010-9035-6-e DE-627 ger DE-627 rakwb eng Espinosa-Duró, Virginia verfasserin aut Beyond Cognitive Signals 2010 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science+Business Media, LLC 2010 Abstract Although audio-visual human systems have several well-known limitations, artificial sensors can measure information beyond our limits. What would happen if we were able to overcome our limitations? Would we be able to obtain a better knowledge of our environment? Or the information beyond our limits is redundant? In this paper, we compare infrared, thermal and visible images from an information theory point of view. We have acquired a small database and compared several measurements over these images. While infrasounds and ultrasounds are not directly applicable, for instance, to speaker recognition due to the impossibility of human beings generating sounds in these frequencies, this is not the case with image signals beyond the visible spectrum for face recognition. We have observed that visible, near-infrared and thermal images contain a small amount of redundancy (less than 1,55 bits). Image analysis (dpeaa)DE-He213 Information theory (dpeaa)DE-He213 Face (dpeaa)DE-He213 Thermal image (dpeaa)DE-He213 Visible image (dpeaa)DE-He213 Near-infrared image (dpeaa)DE-He213 Faundez-Zanuy, Marcos aut Mekyska, Jiří aut Enthalten in Cognitive Computation New York, NY : Springer, 2009 3(2010), 2 vom: 20. März, Seite 374-381 (DE-627)594779472 (DE-600)2486574-6 1866-9964 nnns volume:3 year:2010 number:2 day:20 month:03 pages:374-381 https://dx.doi.org/10.1007/s12559-010-9035-6 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_101 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 3 2010 2 20 03 374-381
spelling	10.1007/s12559-010-9035-6 doi (DE-627)SPR026477084 (SPR)s12559-010-9035-6-e DE-627 ger DE-627 rakwb eng Espinosa-Duró, Virginia verfasserin aut Beyond Cognitive Signals 2010 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science+Business Media, LLC 2010 Abstract Although audio-visual human systems have several well-known limitations, artificial sensors can measure information beyond our limits. What would happen if we were able to overcome our limitations? Would we be able to obtain a better knowledge of our environment? Or the information beyond our limits is redundant? In this paper, we compare infrared, thermal and visible images from an information theory point of view. We have acquired a small database and compared several measurements over these images. While infrasounds and ultrasounds are not directly applicable, for instance, to speaker recognition due to the impossibility of human beings generating sounds in these frequencies, this is not the case with image signals beyond the visible spectrum for face recognition. We have observed that visible, near-infrared and thermal images contain a small amount of redundancy (less than 1,55 bits). Image analysis (dpeaa)DE-He213 Information theory (dpeaa)DE-He213 Face (dpeaa)DE-He213 Thermal image (dpeaa)DE-He213 Visible image (dpeaa)DE-He213 Near-infrared image (dpeaa)DE-He213 Faundez-Zanuy, Marcos aut Mekyska, Jiří aut Enthalten in Cognitive Computation New York, NY : Springer, 2009 3(2010), 2 vom: 20. März, Seite 374-381 (DE-627)594779472 (DE-600)2486574-6 1866-9964 nnns volume:3 year:2010 number:2 day:20 month:03 pages:374-381 https://dx.doi.org/10.1007/s12559-010-9035-6 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_101 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 3 2010 2 20 03 374-381
allfields_unstemmed	10.1007/s12559-010-9035-6 doi (DE-627)SPR026477084 (SPR)s12559-010-9035-6-e DE-627 ger DE-627 rakwb eng Espinosa-Duró, Virginia verfasserin aut Beyond Cognitive Signals 2010 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science+Business Media, LLC 2010 Abstract Although audio-visual human systems have several well-known limitations, artificial sensors can measure information beyond our limits. What would happen if we were able to overcome our limitations? Would we be able to obtain a better knowledge of our environment? Or the information beyond our limits is redundant? In this paper, we compare infrared, thermal and visible images from an information theory point of view. We have acquired a small database and compared several measurements over these images. While infrasounds and ultrasounds are not directly applicable, for instance, to speaker recognition due to the impossibility of human beings generating sounds in these frequencies, this is not the case with image signals beyond the visible spectrum for face recognition. We have observed that visible, near-infrared and thermal images contain a small amount of redundancy (less than 1,55 bits). Image analysis (dpeaa)DE-He213 Information theory (dpeaa)DE-He213 Face (dpeaa)DE-He213 Thermal image (dpeaa)DE-He213 Visible image (dpeaa)DE-He213 Near-infrared image (dpeaa)DE-He213 Faundez-Zanuy, Marcos aut Mekyska, Jiří aut Enthalten in Cognitive Computation New York, NY : Springer, 2009 3(2010), 2 vom: 20. März, Seite 374-381 (DE-627)594779472 (DE-600)2486574-6 1866-9964 nnns volume:3 year:2010 number:2 day:20 month:03 pages:374-381 https://dx.doi.org/10.1007/s12559-010-9035-6 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_101 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 3 2010 2 20 03 374-381
allfieldsGer	10.1007/s12559-010-9035-6 doi (DE-627)SPR026477084 (SPR)s12559-010-9035-6-e DE-627 ger DE-627 rakwb eng Espinosa-Duró, Virginia verfasserin aut Beyond Cognitive Signals 2010 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science+Business Media, LLC 2010 Abstract Although audio-visual human systems have several well-known limitations, artificial sensors can measure information beyond our limits. What would happen if we were able to overcome our limitations? Would we be able to obtain a better knowledge of our environment? Or the information beyond our limits is redundant? In this paper, we compare infrared, thermal and visible images from an information theory point of view. We have acquired a small database and compared several measurements over these images. While infrasounds and ultrasounds are not directly applicable, for instance, to speaker recognition due to the impossibility of human beings generating sounds in these frequencies, this is not the case with image signals beyond the visible spectrum for face recognition. We have observed that visible, near-infrared and thermal images contain a small amount of redundancy (less than 1,55 bits). Image analysis (dpeaa)DE-He213 Information theory (dpeaa)DE-He213 Face (dpeaa)DE-He213 Thermal image (dpeaa)DE-He213 Visible image (dpeaa)DE-He213 Near-infrared image (dpeaa)DE-He213 Faundez-Zanuy, Marcos aut Mekyska, Jiří aut Enthalten in Cognitive Computation New York, NY : Springer, 2009 3(2010), 2 vom: 20. März, Seite 374-381 (DE-627)594779472 (DE-600)2486574-6 1866-9964 nnns volume:3 year:2010 number:2 day:20 month:03 pages:374-381 https://dx.doi.org/10.1007/s12559-010-9035-6 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_101 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 3 2010 2 20 03 374-381
allfieldsSound	10.1007/s12559-010-9035-6 doi (DE-627)SPR026477084 (SPR)s12559-010-9035-6-e DE-627 ger DE-627 rakwb eng Espinosa-Duró, Virginia verfasserin aut Beyond Cognitive Signals 2010 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science+Business Media, LLC 2010 Abstract Although audio-visual human systems have several well-known limitations, artificial sensors can measure information beyond our limits. What would happen if we were able to overcome our limitations? Would we be able to obtain a better knowledge of our environment? Or the information beyond our limits is redundant? In this paper, we compare infrared, thermal and visible images from an information theory point of view. We have acquired a small database and compared several measurements over these images. While infrasounds and ultrasounds are not directly applicable, for instance, to speaker recognition due to the impossibility of human beings generating sounds in these frequencies, this is not the case with image signals beyond the visible spectrum for face recognition. We have observed that visible, near-infrared and thermal images contain a small amount of redundancy (less than 1,55 bits). Image analysis (dpeaa)DE-He213 Information theory (dpeaa)DE-He213 Face (dpeaa)DE-He213 Thermal image (dpeaa)DE-He213 Visible image (dpeaa)DE-He213 Near-infrared image (dpeaa)DE-He213 Faundez-Zanuy, Marcos aut Mekyska, Jiří aut Enthalten in Cognitive Computation New York, NY : Springer, 2009 3(2010), 2 vom: 20. März, Seite 374-381 (DE-627)594779472 (DE-600)2486574-6 1866-9964 nnns volume:3 year:2010 number:2 day:20 month:03 pages:374-381 https://dx.doi.org/10.1007/s12559-010-9035-6 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_101 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 3 2010 2 20 03 374-381
language	English
source	Enthalten in Cognitive Computation 3(2010), 2 vom: 20. März, Seite 374-381 volume:3 year:2010 number:2 day:20 month:03 pages:374-381
sourceStr	Enthalten in Cognitive Computation 3(2010), 2 vom: 20. März, Seite 374-381 volume:3 year:2010 number:2 day:20 month:03 pages:374-381
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Image analysis Information theory Face Thermal image Visible image Near-infrared image
isfreeaccess_bool	false
container_title	Cognitive Computation
authorswithroles_txt_mv	Espinosa-Duró, Virginia @@aut@@ Faundez-Zanuy, Marcos @@aut@@ Mekyska, Jiří @@aut@@
publishDateDaySort_date	2010-03-20T00:00:00Z
hierarchy_top_id	594779472
id	SPR026477084
language_de	englisch
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author	Espinosa-Duró, Virginia
spellingShingle	Espinosa-Duró, Virginia misc Image analysis misc Information theory misc Face misc Thermal image misc Visible image misc Near-infrared image Beyond Cognitive Signals
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topic_title	Beyond Cognitive Signals Image analysis (dpeaa)DE-He213 Information theory (dpeaa)DE-He213 Face (dpeaa)DE-He213 Thermal image (dpeaa)DE-He213 Visible image (dpeaa)DE-He213 Near-infrared image (dpeaa)DE-He213
topic	misc Image analysis misc Information theory misc Face misc Thermal image misc Visible image misc Near-infrared image
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title_full	Beyond Cognitive Signals
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author_browse	Espinosa-Duró, Virginia Faundez-Zanuy, Marcos Mekyska, Jiří
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title_sort	beyond cognitive signals
title_auth	Beyond Cognitive Signals
abstract	Abstract Although audio-visual human systems have several well-known limitations, artificial sensors can measure information beyond our limits. What would happen if we were able to overcome our limitations? Would we be able to obtain a better knowledge of our environment? Or the information beyond our limits is redundant? In this paper, we compare infrared, thermal and visible images from an information theory point of view. We have acquired a small database and compared several measurements over these images. While infrasounds and ultrasounds are not directly applicable, for instance, to speaker recognition due to the impossibility of human beings generating sounds in these frequencies, this is not the case with image signals beyond the visible spectrum for face recognition. We have observed that visible, near-infrared and thermal images contain a small amount of redundancy (less than 1,55 bits). © Springer Science+Business Media, LLC 2010
abstractGer	Abstract Although audio-visual human systems have several well-known limitations, artificial sensors can measure information beyond our limits. What would happen if we were able to overcome our limitations? Would we be able to obtain a better knowledge of our environment? Or the information beyond our limits is redundant? In this paper, we compare infrared, thermal and visible images from an information theory point of view. We have acquired a small database and compared several measurements over these images. While infrasounds and ultrasounds are not directly applicable, for instance, to speaker recognition due to the impossibility of human beings generating sounds in these frequencies, this is not the case with image signals beyond the visible spectrum for face recognition. We have observed that visible, near-infrared and thermal images contain a small amount of redundancy (less than 1,55 bits). © Springer Science+Business Media, LLC 2010
abstract_unstemmed	Abstract Although audio-visual human systems have several well-known limitations, artificial sensors can measure information beyond our limits. What would happen if we were able to overcome our limitations? Would we be able to obtain a better knowledge of our environment? Or the information beyond our limits is redundant? In this paper, we compare infrared, thermal and visible images from an information theory point of view. We have acquired a small database and compared several measurements over these images. While infrasounds and ultrasounds are not directly applicable, for instance, to speaker recognition due to the impossibility of human beings generating sounds in these frequencies, this is not the case with image signals beyond the visible spectrum for face recognition. We have observed that visible, near-infrared and thermal images contain a small amount of redundancy (less than 1,55 bits). © Springer Science+Business Media, LLC 2010
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title_short	Beyond Cognitive Signals
url	https://dx.doi.org/10.1007/s12559-010-9035-6
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up_date	2024-07-03T21:01:23.792Z
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