Cast shadow detection for moving objects based on binocular stereo vision

Abstract A novel cast shadow detection approach was proposed. A stereo vision system was used to capture images instead of traditional single camera. It was based on an assumption that cast shadows were on a special plane. The image obtained from one camera was inversely projected to the plane and t...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Peng, Qi [verfasserIn] Zhong, Si-dong Tu, Li-fen

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2014

Anmerkung:	© Central South University Press and Springer-Verlag Berlin Heidelberg 2014

Übergeordnetes Werk:	Enthalten in: Journal of Central South University of Technology - Changsha : CSUT, 1994, 21(2014), 2 vom: Feb., Seite 651-658
Übergeordnetes Werk:	volume:21 ; year:2014 ; number:2 ; month:02 ; pages:651-658

Links:	Volltext

DOI / URN:	10.1007/s11771-014-1985-5

Katalog-ID:	SPR022362509

Internformat


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245	1	0	\|a Cast shadow detection for moving objects based on binocular stereo vision
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520			\|a Abstract A novel cast shadow detection approach was proposed. A stereo vision system was used to capture images instead of traditional single camera. It was based on an assumption that cast shadows were on a special plane. The image obtained from one camera was inversely projected to the plane and then transformed to the view from another camera. The points on the plane shared the same position between original image and the transformed image. As a result, the cast shadows can be detected. In order to improve the efficiency of cast shadow detection and decrease computational complexity, the obvious object areas in CIELAB color space were removed and the potential shadow areas were obtained. Experimental results demonstrate that the proposed approach can detect cast shadows accurately even under various illuminations.
700	1		\|a Zhong, Si-dong \|4 aut
700	1		\|a Tu, Li-fen \|4 aut
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912			\|a GBV_ILN_32
912			\|a GBV_ILN_39
912			\|a GBV_ILN_40
912			\|a GBV_ILN_60
912			\|a GBV_ILN_62
912			\|a GBV_ILN_63
912			\|a GBV_ILN_65
912			\|a GBV_ILN_69
912			\|a GBV_ILN_70
912			\|a GBV_ILN_73
912			\|a GBV_ILN_74
912			\|a GBV_ILN_90
912			\|a GBV_ILN_95
912			\|a GBV_ILN_100
912			\|a GBV_ILN_105
912			\|a GBV_ILN_110
912			\|a GBV_ILN_120
912			\|a GBV_ILN_121
912			\|a GBV_ILN_138
912			\|a GBV_ILN_150
912			\|a GBV_ILN_151
912			\|a GBV_ILN_152
912			\|a GBV_ILN_161
912			\|a GBV_ILN_170
912			\|a GBV_ILN_171
912			\|a GBV_ILN_187
912			\|a GBV_ILN_206
912			\|a GBV_ILN_213
912			\|a GBV_ILN_224
912			\|a GBV_ILN_230
912			\|a GBV_ILN_250
912			\|a GBV_ILN_281
912			\|a GBV_ILN_285
912			\|a GBV_ILN_293
912			\|a GBV_ILN_370
912			\|a GBV_ILN_374
912			\|a GBV_ILN_602
912			\|a GBV_ILN_647
912			\|a GBV_ILN_702
912			\|a GBV_ILN_2001
912			\|a GBV_ILN_2003
912			\|a GBV_ILN_2005
912			\|a GBV_ILN_2006
912			\|a GBV_ILN_2007
912			\|a GBV_ILN_2008
912			\|a GBV_ILN_2009
912			\|a GBV_ILN_2010
912			\|a GBV_ILN_2011
912			\|a GBV_ILN_2014
912			\|a GBV_ILN_2015
912			\|a GBV_ILN_2018
912			\|a GBV_ILN_2020
912			\|a GBV_ILN_2021
912			\|a GBV_ILN_2025
912			\|a GBV_ILN_2026
912			\|a GBV_ILN_2027
912			\|a GBV_ILN_2031
912			\|a GBV_ILN_2034
912			\|a GBV_ILN_2036
912			\|a GBV_ILN_2037
912			\|a GBV_ILN_2048
912			\|a GBV_ILN_2050
912			\|a GBV_ILN_2055
912			\|a GBV_ILN_2056
912			\|a GBV_ILN_2057
912			\|a GBV_ILN_2059
912			\|a GBV_ILN_2061
912			\|a GBV_ILN_2064
912			\|a GBV_ILN_2065
912			\|a GBV_ILN_2068
912			\|a GBV_ILN_2088
912			\|a GBV_ILN_2093
912			\|a GBV_ILN_2110
912			\|a GBV_ILN_2111
912			\|a GBV_ILN_2113
912			\|a GBV_ILN_2119
912			\|a GBV_ILN_2129
912			\|a GBV_ILN_2147
912			\|a GBV_ILN_2148
912			\|a GBV_ILN_2152
912			\|a GBV_ILN_2190
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912			\|a GBV_ILN_2470
912			\|a GBV_ILN_2507
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912			\|a GBV_ILN_2548
912			\|a GBV_ILN_2700
912			\|a GBV_ILN_2817
912			\|a GBV_ILN_4012
912			\|a GBV_ILN_4035
912			\|a GBV_ILN_4037
912			\|a GBV_ILN_4046
912			\|a GBV_ILN_4112
912			\|a GBV_ILN_4125
912			\|a GBV_ILN_4126
912			\|a GBV_ILN_4242
912			\|a GBV_ILN_4246
912			\|a GBV_ILN_4251
912			\|a GBV_ILN_4277
912			\|a GBV_ILN_4305
912			\|a GBV_ILN_4306
912			\|a GBV_ILN_4307
912			\|a GBV_ILN_4313
912			\|a GBV_ILN_4322
912			\|a GBV_ILN_4323
912			\|a GBV_ILN_4324
912			\|a GBV_ILN_4325
912			\|a GBV_ILN_4326
912			\|a GBV_ILN_4333
912			\|a GBV_ILN_4335
912			\|a GBV_ILN_4336
912			\|a GBV_ILN_4338
912			\|a GBV_ILN_4346
912			\|a GBV_ILN_4367
912			\|a GBV_ILN_4392
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publishDate	2014
allfields	10.1007/s11771-014-1985-5 doi (DE-627)SPR022362509 (SPR)s11771-014-1985-5-e DE-627 ger DE-627 rakwb eng Peng, Qi verfasserin aut Cast shadow detection for moving objects based on binocular stereo vision 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Central South University Press and Springer-Verlag Berlin Heidelberg 2014 Abstract A novel cast shadow detection approach was proposed. A stereo vision system was used to capture images instead of traditional single camera. It was based on an assumption that cast shadows were on a special plane. The image obtained from one camera was inversely projected to the plane and then transformed to the view from another camera. The points on the plane shared the same position between original image and the transformed image. As a result, the cast shadows can be detected. In order to improve the efficiency of cast shadow detection and decrease computational complexity, the obvious object areas in CIELAB color space were removed and the potential shadow areas were obtained. Experimental results demonstrate that the proposed approach can detect cast shadows accurately even under various illuminations. Zhong, Si-dong aut Tu, Li-fen aut Enthalten in Journal of Central South University of Technology Changsha : CSUT, 1994 21(2014), 2 vom: Feb., Seite 651-658 (DE-627)531203670 (DE-600)2324899-3 1993-0666 nnns volume:21 year:2014 number:2 month:02 pages:651-658 https://dx.doi.org/10.1007/s11771-014-1985-5 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_121 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_206 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_374 GBV_ILN_602 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 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_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2036 GBV_ILN_2037 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2119 GBV_ILN_2129 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2700 GBV_ILN_2817 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_4251 GBV_ILN_4277 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_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4346 GBV_ILN_4367 GBV_ILN_4392 GBV_ILN_4393 GBV_ILN_4753 AR 21 2014 2 02 651-658
spelling	10.1007/s11771-014-1985-5 doi (DE-627)SPR022362509 (SPR)s11771-014-1985-5-e DE-627 ger DE-627 rakwb eng Peng, Qi verfasserin aut Cast shadow detection for moving objects based on binocular stereo vision 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Central South University Press and Springer-Verlag Berlin Heidelberg 2014 Abstract A novel cast shadow detection approach was proposed. A stereo vision system was used to capture images instead of traditional single camera. It was based on an assumption that cast shadows were on a special plane. The image obtained from one camera was inversely projected to the plane and then transformed to the view from another camera. The points on the plane shared the same position between original image and the transformed image. As a result, the cast shadows can be detected. In order to improve the efficiency of cast shadow detection and decrease computational complexity, the obvious object areas in CIELAB color space were removed and the potential shadow areas were obtained. Experimental results demonstrate that the proposed approach can detect cast shadows accurately even under various illuminations. Zhong, Si-dong aut Tu, Li-fen aut Enthalten in Journal of Central South University of Technology Changsha : CSUT, 1994 21(2014), 2 vom: Feb., Seite 651-658 (DE-627)531203670 (DE-600)2324899-3 1993-0666 nnns volume:21 year:2014 number:2 month:02 pages:651-658 https://dx.doi.org/10.1007/s11771-014-1985-5 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_121 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_206 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_374 GBV_ILN_602 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 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_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2036 GBV_ILN_2037 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2119 GBV_ILN_2129 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2700 GBV_ILN_2817 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_4251 GBV_ILN_4277 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_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4346 GBV_ILN_4367 GBV_ILN_4392 GBV_ILN_4393 GBV_ILN_4753 AR 21 2014 2 02 651-658
allfields_unstemmed	10.1007/s11771-014-1985-5 doi (DE-627)SPR022362509 (SPR)s11771-014-1985-5-e DE-627 ger DE-627 rakwb eng Peng, Qi verfasserin aut Cast shadow detection for moving objects based on binocular stereo vision 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Central South University Press and Springer-Verlag Berlin Heidelberg 2014 Abstract A novel cast shadow detection approach was proposed. A stereo vision system was used to capture images instead of traditional single camera. It was based on an assumption that cast shadows were on a special plane. The image obtained from one camera was inversely projected to the plane and then transformed to the view from another camera. The points on the plane shared the same position between original image and the transformed image. As a result, the cast shadows can be detected. In order to improve the efficiency of cast shadow detection and decrease computational complexity, the obvious object areas in CIELAB color space were removed and the potential shadow areas were obtained. Experimental results demonstrate that the proposed approach can detect cast shadows accurately even under various illuminations. Zhong, Si-dong aut Tu, Li-fen aut Enthalten in Journal of Central South University of Technology Changsha : CSUT, 1994 21(2014), 2 vom: Feb., Seite 651-658 (DE-627)531203670 (DE-600)2324899-3 1993-0666 nnns volume:21 year:2014 number:2 month:02 pages:651-658 https://dx.doi.org/10.1007/s11771-014-1985-5 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_121 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_206 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_374 GBV_ILN_602 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 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_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2036 GBV_ILN_2037 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2119 GBV_ILN_2129 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2700 GBV_ILN_2817 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_4251 GBV_ILN_4277 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_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4346 GBV_ILN_4367 GBV_ILN_4392 GBV_ILN_4393 GBV_ILN_4753 AR 21 2014 2 02 651-658
allfieldsGer	10.1007/s11771-014-1985-5 doi (DE-627)SPR022362509 (SPR)s11771-014-1985-5-e DE-627 ger DE-627 rakwb eng Peng, Qi verfasserin aut Cast shadow detection for moving objects based on binocular stereo vision 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Central South University Press and Springer-Verlag Berlin Heidelberg 2014 Abstract A novel cast shadow detection approach was proposed. A stereo vision system was used to capture images instead of traditional single camera. It was based on an assumption that cast shadows were on a special plane. The image obtained from one camera was inversely projected to the plane and then transformed to the view from another camera. The points on the plane shared the same position between original image and the transformed image. As a result, the cast shadows can be detected. In order to improve the efficiency of cast shadow detection and decrease computational complexity, the obvious object areas in CIELAB color space were removed and the potential shadow areas were obtained. Experimental results demonstrate that the proposed approach can detect cast shadows accurately even under various illuminations. Zhong, Si-dong aut Tu, Li-fen aut Enthalten in Journal of Central South University of Technology Changsha : CSUT, 1994 21(2014), 2 vom: Feb., Seite 651-658 (DE-627)531203670 (DE-600)2324899-3 1993-0666 nnns volume:21 year:2014 number:2 month:02 pages:651-658 https://dx.doi.org/10.1007/s11771-014-1985-5 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_121 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_206 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_374 GBV_ILN_602 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 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_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2036 GBV_ILN_2037 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2119 GBV_ILN_2129 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2700 GBV_ILN_2817 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_4251 GBV_ILN_4277 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_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4346 GBV_ILN_4367 GBV_ILN_4392 GBV_ILN_4393 GBV_ILN_4753 AR 21 2014 2 02 651-658
allfieldsSound	10.1007/s11771-014-1985-5 doi (DE-627)SPR022362509 (SPR)s11771-014-1985-5-e DE-627 ger DE-627 rakwb eng Peng, Qi verfasserin aut Cast shadow detection for moving objects based on binocular stereo vision 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Central South University Press and Springer-Verlag Berlin Heidelberg 2014 Abstract A novel cast shadow detection approach was proposed. A stereo vision system was used to capture images instead of traditional single camera. It was based on an assumption that cast shadows were on a special plane. The image obtained from one camera was inversely projected to the plane and then transformed to the view from another camera. The points on the plane shared the same position between original image and the transformed image. As a result, the cast shadows can be detected. In order to improve the efficiency of cast shadow detection and decrease computational complexity, the obvious object areas in CIELAB color space were removed and the potential shadow areas were obtained. Experimental results demonstrate that the proposed approach can detect cast shadows accurately even under various illuminations. Zhong, Si-dong aut Tu, Li-fen aut Enthalten in Journal of Central South University of Technology Changsha : CSUT, 1994 21(2014), 2 vom: Feb., Seite 651-658 (DE-627)531203670 (DE-600)2324899-3 1993-0666 nnns volume:21 year:2014 number:2 month:02 pages:651-658 https://dx.doi.org/10.1007/s11771-014-1985-5 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_121 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_206 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_374 GBV_ILN_602 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 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_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2036 GBV_ILN_2037 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2119 GBV_ILN_2129 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2700 GBV_ILN_2817 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_4251 GBV_ILN_4277 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_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4346 GBV_ILN_4367 GBV_ILN_4392 GBV_ILN_4393 GBV_ILN_4753 AR 21 2014 2 02 651-658
language	English
source	Enthalten in Journal of Central South University of Technology 21(2014), 2 vom: Feb., Seite 651-658 volume:21 year:2014 number:2 month:02 pages:651-658
sourceStr	Enthalten in Journal of Central South University of Technology 21(2014), 2 vom: Feb., Seite 651-658 volume:21 year:2014 number:2 month:02 pages:651-658
format_phy_str_mv	Article
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container_title	Journal of Central South University of Technology
authorswithroles_txt_mv	Peng, Qi @@aut@@ Zhong, Si-dong @@aut@@ Tu, Li-fen @@aut@@
publishDateDaySort_date	2014-02-01T00:00:00Z
hierarchy_top_id	531203670
id	SPR022362509
language_de	englisch
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author	Peng, Qi
spellingShingle	Peng, Qi Cast shadow detection for moving objects based on binocular stereo vision
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title	Cast shadow detection for moving objects based on binocular stereo vision
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title_full	Cast shadow detection for moving objects based on binocular stereo vision
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title_sort	cast shadow detection for moving objects based on binocular stereo vision
title_auth	Cast shadow detection for moving objects based on binocular stereo vision
abstract	Abstract A novel cast shadow detection approach was proposed. A stereo vision system was used to capture images instead of traditional single camera. It was based on an assumption that cast shadows were on a special plane. The image obtained from one camera was inversely projected to the plane and then transformed to the view from another camera. The points on the plane shared the same position between original image and the transformed image. As a result, the cast shadows can be detected. In order to improve the efficiency of cast shadow detection and decrease computational complexity, the obvious object areas in CIELAB color space were removed and the potential shadow areas were obtained. Experimental results demonstrate that the proposed approach can detect cast shadows accurately even under various illuminations. © Central South University Press and Springer-Verlag Berlin Heidelberg 2014
abstractGer	Abstract A novel cast shadow detection approach was proposed. A stereo vision system was used to capture images instead of traditional single camera. It was based on an assumption that cast shadows were on a special plane. The image obtained from one camera was inversely projected to the plane and then transformed to the view from another camera. The points on the plane shared the same position between original image and the transformed image. As a result, the cast shadows can be detected. In order to improve the efficiency of cast shadow detection and decrease computational complexity, the obvious object areas in CIELAB color space were removed and the potential shadow areas were obtained. Experimental results demonstrate that the proposed approach can detect cast shadows accurately even under various illuminations. © Central South University Press and Springer-Verlag Berlin Heidelberg 2014
abstract_unstemmed	Abstract A novel cast shadow detection approach was proposed. A stereo vision system was used to capture images instead of traditional single camera. It was based on an assumption that cast shadows were on a special plane. The image obtained from one camera was inversely projected to the plane and then transformed to the view from another camera. The points on the plane shared the same position between original image and the transformed image. As a result, the cast shadows can be detected. In order to improve the efficiency of cast shadow detection and decrease computational complexity, the obvious object areas in CIELAB color space were removed and the potential shadow areas were obtained. Experimental results demonstrate that the proposed approach can detect cast shadows accurately even under various illuminations. © Central South University Press and Springer-Verlag Berlin Heidelberg 2014
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title_short	Cast shadow detection for moving objects based on binocular stereo vision
url	https://dx.doi.org/10.1007/s11771-014-1985-5
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Cast shadow detection for moving objects based on binocular stereo vision

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