Spatio-Temporal Grabcut human segmentation for face and pose recovery

Antonio Hernández; Miguel Reyes; Sergio Escalera; Petia Radeva

doi:10.1109/CVPRW.2010.5543824

Spatio-Temporal Grabcut human segmentation for face and pose recovery

Antonio Hernández^*, Miguel Reyes, Sergio Escalera, Petia Radeva

^*Corresponding author for this work

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

30 Citations (Scopus)

Abstract

In this paper, we present a full-automatic Spatio- Temporal GrabCut human segmentation methodology. GrabCut initialization is performed by a HOG-based subject detection, face detection, and skin color model for seed initialization. Spatial information is included by means of Mean Shift clustering whereas temporal coherence is considered by the historical of Gaussian Mixture Models. Moreover, human segmentation is combined with Shape and Active Appearance Models to perform full face and pose recovery. Results over public data sets as well as proper human action base show a robust segmentation and recovery of both face and pose using the presented methodology.

Original language	English
Title of host publication	2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, CVPRW 2010
Number of pages	8
Publication date	2010
Pages	33-40
Article number	5543824
ISBN (Print)	9781424470297
DOIs	https://doi.org/10.1109/CVPRW.2010.5543824
Publication status	Published - 2010
Externally published	Yes
Event	2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, CVPRW 2010 - San Francisco, CA, United States Duration: 13 Jun 2010 → 18 Jun 2010

Conference

Conference	2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, CVPRW 2010
Country/Territory	United States
City	San Francisco, CA
Period	13/06/2010 → 18/06/2010

Series	2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, CVPRW 2010

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10.1109/CVPRW.2010.5543824

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title = "Spatio-Temporal Grabcut human segmentation for face and pose recovery",

abstract = "In this paper, we present a full-automatic Spatio- Temporal GrabCut human segmentation methodology. GrabCut initialization is performed by a HOG-based subject detection, face detection, and skin color model for seed initialization. Spatial information is included by means of Mean Shift clustering whereas temporal coherence is considered by the historical of Gaussian Mixture Models. Moreover, human segmentation is combined with Shape and Active Appearance Models to perform full face and pose recovery. Results over public data sets as well as proper human action base show a robust segmentation and recovery of both face and pose using the presented methodology.",

author = "Antonio Hern{\'a}ndez and Miguel Reyes and Sergio Escalera and Petia Radeva",

year = "2010",

doi = "10.1109/CVPRW.2010.5543824",

language = "English",

isbn = "9781424470297",

series = "2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, CVPRW 2010",

pages = "33--40",

booktitle = "2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, CVPRW 2010",

note = "2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, CVPRW 2010 ; Conference date: 13-06-2010 Through 18-06-2010",

}

Hernández, A, Reyes, M, Escalera, S & Radeva, P 2010, Spatio-Temporal Grabcut human segmentation for face and pose recovery. in 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, CVPRW 2010., 5543824, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, CVPRW 2010, pp. 33-40, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, CVPRW 2010, San Francisco, CA, United States, 13/06/2010. https://doi.org/10.1109/CVPRW.2010.5543824

Spatio-Temporal Grabcut human segmentation for face and pose recovery. / Hernández, Antonio; Reyes, Miguel; Escalera, Sergio et al.
2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, CVPRW 2010. 2010. p. 33-40 5543824 (2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, CVPRW 2010).

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

TY - GEN

T1 - Spatio-Temporal Grabcut human segmentation for face and pose recovery

AU - Hernández, Antonio

AU - Reyes, Miguel

AU - Escalera, Sergio

AU - Radeva, Petia

PY - 2010

Y1 - 2010

N2 - In this paper, we present a full-automatic Spatio- Temporal GrabCut human segmentation methodology. GrabCut initialization is performed by a HOG-based subject detection, face detection, and skin color model for seed initialization. Spatial information is included by means of Mean Shift clustering whereas temporal coherence is considered by the historical of Gaussian Mixture Models. Moreover, human segmentation is combined with Shape and Active Appearance Models to perform full face and pose recovery. Results over public data sets as well as proper human action base show a robust segmentation and recovery of both face and pose using the presented methodology.

AB - In this paper, we present a full-automatic Spatio- Temporal GrabCut human segmentation methodology. GrabCut initialization is performed by a HOG-based subject detection, face detection, and skin color model for seed initialization. Spatial information is included by means of Mean Shift clustering whereas temporal coherence is considered by the historical of Gaussian Mixture Models. Moreover, human segmentation is combined with Shape and Active Appearance Models to perform full face and pose recovery. Results over public data sets as well as proper human action base show a robust segmentation and recovery of both face and pose using the presented methodology.

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U2 - 10.1109/CVPRW.2010.5543824

DO - 10.1109/CVPRW.2010.5543824

M3 - Article in proceeding

AN - SCOPUS:77956547048

SN - 9781424470297

T3 - 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, CVPRW 2010

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EP - 40

BT - 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, CVPRW 2010

T2 - 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, CVPRW 2010

Y2 - 13 June 2010 through 18 June 2010

ER -

Hernández A, Reyes M, Escalera S, Radeva P. Spatio-Temporal Grabcut human segmentation for face and pose recovery. In 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, CVPRW 2010. 2010. p. 33-40. 5543824. (2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, CVPRW 2010). doi: 10.1109/CVPRW.2010.5543824

Spatio-Temporal Grabcut human segmentation for face and pose recovery

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