Estimation of 3-D human body posture via co-registration of 3-D human model and sequential stereo information
Abstract In this paper, we present a technique for estimating three-dimensional (3-D) human body posture from a set of sequential stereo images. We estimated the pixel displacements of stereo image pairs to reconstruct 3-D information. We modeled the human body with a set of ellipsoids connected by...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Thang, Nguyen Duc [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2010 |
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| Schlagwörter: |
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| Anmerkung: |
© Springer Science+Business Media, LLC 2010 |
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| Übergeordnetes Werk: |
Enthalten in: Applied intelligence - Springer US, 1991, 35(2010), 2 vom: 20. Feb., Seite 163-177 |
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| Übergeordnetes Werk: |
volume:35 ; year:2010 ; number:2 ; day:20 ; month:02 ; pages:163-177 |
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| DOI / URN: |
10.1007/s10489-009-0209-4 |
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OLC2066096407 |
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| 520 | |a Abstract In this paper, we present a technique for estimating three-dimensional (3-D) human body posture from a set of sequential stereo images. We estimated the pixel displacements of stereo image pairs to reconstruct 3-D information. We modeled the human body with a set of ellipsoids connected by kinematic chains and parameterized with rotational angles at each body joint. To estimate human posture from the 3-D data, we developed a new algorithm based on expectation maximization (EM) with two-step iterations, assigning the 3-D data to different body parts and refining the kinematic parameters to fit the 3-D model to the data. The algorithm is iterated until it converges on the correct posture. Experimental results with synthetic and real data demonstrate that our method is capable of reconstructing 3-D human posture from stereo images. Our method is robust and generic; any useful information for locating the body parts can be integrated into our framework to improve the outcomes. | ||
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10.1007/s10489-009-0209-4 doi (DE-627)OLC2066096407 (DE-He213)s10489-009-0209-4-p DE-627 ger DE-627 rakwb eng 004 VZ Thang, Nguyen Duc verfasserin aut Estimation of 3-D human body posture via co-registration of 3-D human model and sequential stereo information 2010 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC 2010 Abstract In this paper, we present a technique for estimating three-dimensional (3-D) human body posture from a set of sequential stereo images. We estimated the pixel displacements of stereo image pairs to reconstruct 3-D information. We modeled the human body with a set of ellipsoids connected by kinematic chains and parameterized with rotational angles at each body joint. To estimate human posture from the 3-D data, we developed a new algorithm based on expectation maximization (EM) with two-step iterations, assigning the 3-D data to different body parts and refining the kinematic parameters to fit the 3-D model to the data. The algorithm is iterated until it converges on the correct posture. Experimental results with synthetic and real data demonstrate that our method is capable of reconstructing 3-D human posture from stereo images. Our method is robust and generic; any useful information for locating the body parts can be integrated into our framework to improve the outcomes. Estimation of 3-D human body posture Stereo images Articulated human body model Kim, Tae-Seong aut Lee, Young-Koo aut Lee, Sungyoung aut Enthalten in Applied intelligence Springer US, 1991 35(2010), 2 vom: 20. Feb., Seite 163-177 (DE-627)130990515 (DE-600)1080229-0 (DE-576)029154286 0924-669X nnns volume:35 year:2010 number:2 day:20 month:02 pages:163-177 https://doi.org/10.1007/s10489-009-0209-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT GBV_ILN_70 GBV_ILN_130 GBV_ILN_2020 AR 35 2010 2 20 02 163-177 |
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10.1007/s10489-009-0209-4 doi (DE-627)OLC2066096407 (DE-He213)s10489-009-0209-4-p DE-627 ger DE-627 rakwb eng 004 VZ Thang, Nguyen Duc verfasserin aut Estimation of 3-D human body posture via co-registration of 3-D human model and sequential stereo information 2010 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC 2010 Abstract In this paper, we present a technique for estimating three-dimensional (3-D) human body posture from a set of sequential stereo images. We estimated the pixel displacements of stereo image pairs to reconstruct 3-D information. We modeled the human body with a set of ellipsoids connected by kinematic chains and parameterized with rotational angles at each body joint. To estimate human posture from the 3-D data, we developed a new algorithm based on expectation maximization (EM) with two-step iterations, assigning the 3-D data to different body parts and refining the kinematic parameters to fit the 3-D model to the data. The algorithm is iterated until it converges on the correct posture. Experimental results with synthetic and real data demonstrate that our method is capable of reconstructing 3-D human posture from stereo images. Our method is robust and generic; any useful information for locating the body parts can be integrated into our framework to improve the outcomes. Estimation of 3-D human body posture Stereo images Articulated human body model Kim, Tae-Seong aut Lee, Young-Koo aut Lee, Sungyoung aut Enthalten in Applied intelligence Springer US, 1991 35(2010), 2 vom: 20. Feb., Seite 163-177 (DE-627)130990515 (DE-600)1080229-0 (DE-576)029154286 0924-669X nnns volume:35 year:2010 number:2 day:20 month:02 pages:163-177 https://doi.org/10.1007/s10489-009-0209-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT GBV_ILN_70 GBV_ILN_130 GBV_ILN_2020 AR 35 2010 2 20 02 163-177 |
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10.1007/s10489-009-0209-4 doi (DE-627)OLC2066096407 (DE-He213)s10489-009-0209-4-p DE-627 ger DE-627 rakwb eng 004 VZ Thang, Nguyen Duc verfasserin aut Estimation of 3-D human body posture via co-registration of 3-D human model and sequential stereo information 2010 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC 2010 Abstract In this paper, we present a technique for estimating three-dimensional (3-D) human body posture from a set of sequential stereo images. We estimated the pixel displacements of stereo image pairs to reconstruct 3-D information. We modeled the human body with a set of ellipsoids connected by kinematic chains and parameterized with rotational angles at each body joint. To estimate human posture from the 3-D data, we developed a new algorithm based on expectation maximization (EM) with two-step iterations, assigning the 3-D data to different body parts and refining the kinematic parameters to fit the 3-D model to the data. The algorithm is iterated until it converges on the correct posture. Experimental results with synthetic and real data demonstrate that our method is capable of reconstructing 3-D human posture from stereo images. Our method is robust and generic; any useful information for locating the body parts can be integrated into our framework to improve the outcomes. Estimation of 3-D human body posture Stereo images Articulated human body model Kim, Tae-Seong aut Lee, Young-Koo aut Lee, Sungyoung aut Enthalten in Applied intelligence Springer US, 1991 35(2010), 2 vom: 20. Feb., Seite 163-177 (DE-627)130990515 (DE-600)1080229-0 (DE-576)029154286 0924-669X nnns volume:35 year:2010 number:2 day:20 month:02 pages:163-177 https://doi.org/10.1007/s10489-009-0209-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT GBV_ILN_70 GBV_ILN_130 GBV_ILN_2020 AR 35 2010 2 20 02 163-177 |
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10.1007/s10489-009-0209-4 doi (DE-627)OLC2066096407 (DE-He213)s10489-009-0209-4-p DE-627 ger DE-627 rakwb eng 004 VZ Thang, Nguyen Duc verfasserin aut Estimation of 3-D human body posture via co-registration of 3-D human model and sequential stereo information 2010 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC 2010 Abstract In this paper, we present a technique for estimating three-dimensional (3-D) human body posture from a set of sequential stereo images. We estimated the pixel displacements of stereo image pairs to reconstruct 3-D information. We modeled the human body with a set of ellipsoids connected by kinematic chains and parameterized with rotational angles at each body joint. To estimate human posture from the 3-D data, we developed a new algorithm based on expectation maximization (EM) with two-step iterations, assigning the 3-D data to different body parts and refining the kinematic parameters to fit the 3-D model to the data. The algorithm is iterated until it converges on the correct posture. Experimental results with synthetic and real data demonstrate that our method is capable of reconstructing 3-D human posture from stereo images. Our method is robust and generic; any useful information for locating the body parts can be integrated into our framework to improve the outcomes. Estimation of 3-D human body posture Stereo images Articulated human body model Kim, Tae-Seong aut Lee, Young-Koo aut Lee, Sungyoung aut Enthalten in Applied intelligence Springer US, 1991 35(2010), 2 vom: 20. Feb., Seite 163-177 (DE-627)130990515 (DE-600)1080229-0 (DE-576)029154286 0924-669X nnns volume:35 year:2010 number:2 day:20 month:02 pages:163-177 https://doi.org/10.1007/s10489-009-0209-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT GBV_ILN_70 GBV_ILN_130 GBV_ILN_2020 AR 35 2010 2 20 02 163-177 |
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10.1007/s10489-009-0209-4 doi (DE-627)OLC2066096407 (DE-He213)s10489-009-0209-4-p DE-627 ger DE-627 rakwb eng 004 VZ Thang, Nguyen Duc verfasserin aut Estimation of 3-D human body posture via co-registration of 3-D human model and sequential stereo information 2010 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC 2010 Abstract In this paper, we present a technique for estimating three-dimensional (3-D) human body posture from a set of sequential stereo images. We estimated the pixel displacements of stereo image pairs to reconstruct 3-D information. We modeled the human body with a set of ellipsoids connected by kinematic chains and parameterized with rotational angles at each body joint. To estimate human posture from the 3-D data, we developed a new algorithm based on expectation maximization (EM) with two-step iterations, assigning the 3-D data to different body parts and refining the kinematic parameters to fit the 3-D model to the data. The algorithm is iterated until it converges on the correct posture. Experimental results with synthetic and real data demonstrate that our method is capable of reconstructing 3-D human posture from stereo images. Our method is robust and generic; any useful information for locating the body parts can be integrated into our framework to improve the outcomes. Estimation of 3-D human body posture Stereo images Articulated human body model Kim, Tae-Seong aut Lee, Young-Koo aut Lee, Sungyoung aut Enthalten in Applied intelligence Springer US, 1991 35(2010), 2 vom: 20. Feb., Seite 163-177 (DE-627)130990515 (DE-600)1080229-0 (DE-576)029154286 0924-669X nnns volume:35 year:2010 number:2 day:20 month:02 pages:163-177 https://doi.org/10.1007/s10489-009-0209-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT GBV_ILN_70 GBV_ILN_130 GBV_ILN_2020 AR 35 2010 2 20 02 163-177 |
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Estimation of 3-D human body posture via co-registration of 3-D human model and sequential stereo information |
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Abstract In this paper, we present a technique for estimating three-dimensional (3-D) human body posture from a set of sequential stereo images. We estimated the pixel displacements of stereo image pairs to reconstruct 3-D information. We modeled the human body with a set of ellipsoids connected by kinematic chains and parameterized with rotational angles at each body joint. To estimate human posture from the 3-D data, we developed a new algorithm based on expectation maximization (EM) with two-step iterations, assigning the 3-D data to different body parts and refining the kinematic parameters to fit the 3-D model to the data. The algorithm is iterated until it converges on the correct posture. Experimental results with synthetic and real data demonstrate that our method is capable of reconstructing 3-D human posture from stereo images. Our method is robust and generic; any useful information for locating the body parts can be integrated into our framework to improve the outcomes. © Springer Science+Business Media, LLC 2010 |
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Abstract In this paper, we present a technique for estimating three-dimensional (3-D) human body posture from a set of sequential stereo images. We estimated the pixel displacements of stereo image pairs to reconstruct 3-D information. We modeled the human body with a set of ellipsoids connected by kinematic chains and parameterized with rotational angles at each body joint. To estimate human posture from the 3-D data, we developed a new algorithm based on expectation maximization (EM) with two-step iterations, assigning the 3-D data to different body parts and refining the kinematic parameters to fit the 3-D model to the data. The algorithm is iterated until it converges on the correct posture. Experimental results with synthetic and real data demonstrate that our method is capable of reconstructing 3-D human posture from stereo images. Our method is robust and generic; any useful information for locating the body parts can be integrated into our framework to improve the outcomes. © Springer Science+Business Media, LLC 2010 |
| abstract_unstemmed |
Abstract In this paper, we present a technique for estimating three-dimensional (3-D) human body posture from a set of sequential stereo images. We estimated the pixel displacements of stereo image pairs to reconstruct 3-D information. We modeled the human body with a set of ellipsoids connected by kinematic chains and parameterized with rotational angles at each body joint. To estimate human posture from the 3-D data, we developed a new algorithm based on expectation maximization (EM) with two-step iterations, assigning the 3-D data to different body parts and refining the kinematic parameters to fit the 3-D model to the data. The algorithm is iterated until it converges on the correct posture. Experimental results with synthetic and real data demonstrate that our method is capable of reconstructing 3-D human posture from stereo images. Our method is robust and generic; any useful information for locating the body parts can be integrated into our framework to improve the outcomes. © Springer Science+Business Media, LLC 2010 |
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Estimation of 3-D human body posture via co-registration of 3-D human model and sequential stereo information |
| url |
https://doi.org/10.1007/s10489-009-0209-4 |
| remote_bool |
false |
| author2 |
Kim, Tae-Seong Lee, Young-Koo Lee, Sungyoung |
| author2Str |
Kim, Tae-Seong Lee, Young-Koo Lee, Sungyoung |
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130990515 |
| mediatype_str_mv |
n |
| isOA_txt |
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| hochschulschrift_bool |
false |
| doi_str |
10.1007/s10489-009-0209-4 |
| up_date |
2024-07-04T03:45:21.012Z |
| _version_ |
1803618584901976064 |
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