Real-time semantic context labeling for image understanding

M.A.R. Pieck; F. Sommen, van der; S. Zinger; P.H.N. With, de

doi:10.1109/ICIP.2015.7351390

Real-time semantic context labeling for image understanding

M.A.R. Pieck, F. Sommen, van der, S. Zinger, P.H.N. With, de

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review

2 Citaten (Scopus)

1 Downloads (Pure)

Samenvatting

The use of context information in a scene is an important aid for full semantic scene understanding in security and surveillance applications. To this end, this paper presents an innovative semantic context-labeling algorithm for three context classes, trading-off quality and real-time execution. Our system consists of three consecutive stages: image segmentation, region-based feature extraction and classification. We propose the joint use of the features color in HSV space, texture from Gabor filters and spatial context, in combination with the Directional Nearest Neighbor (DNN) method for constructing the undirected graph for segmentation. Compared to recent literature, this combination is over 35 times faster and achieves a coverability rate that is 65% higher.

Originele taal-2	Engels
Titel	Proceedings of the2015 IEEE International Conference on Image Processing (ICIP 2015), 27-30 September 2015, Quebec City, Canada
Plaats van productie	Piscataway
Uitgeverij	Institute of Electrical and Electronics Engineers
Pagina's	3180-3184
ISBN van geprinte versie	978-1-4799-8339-1
DOI's	https://doi.org/10.1109/ICIP.2015.7351390
Status	Gepubliceerd - 2015
Evenement	22nd IEEE International Conference on Image Processing (ICIP 2015) - Quebec, Canada Duur: 27 sep. 2015 → 30 sep. 2015 Congresnummer: 22 http://www.icip2015.org/

Congres

Congres	22nd IEEE International Conference on Image Processing (ICIP 2015)
Verkorte titel	ICIP 2015
Land/Regio	Canada
Stad	Quebec
Periode	27/09/15 → 30/09/15
Ander	IEEE International Conference on Image Processing (ICIP)
Internet adres	http://www.icip2015.org/

Toegang tot document

10.1109/ICIP.2015.7351390

Citeer dit

Pieck, M. A. R., Sommen, van der, F., Zinger, S., & With, de, P. H. N. (2015). Real-time semantic context labeling for image understanding. In Proceedings of the2015 IEEE International Conference on Image Processing (ICIP 2015), 27-30 September 2015, Quebec City, Canada (blz. 3180-3184). Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ICIP.2015.7351390

@inproceedings{77af2b5bfe8e4a51a60cd8ef951538a9,

title = "Real-time semantic context labeling for image understanding",

abstract = "The use of context information in a scene is an important aid for full semantic scene understanding in security and surveillance applications. To this end, this paper presents an innovative semantic context-labeling algorithm for three context classes, trading-off quality and real-time execution. Our system consists of three consecutive stages: image segmentation, region-based feature extraction and classification. We propose the joint use of the features color in HSV space, texture from Gabor filters and spatial context, in combination with the Directional Nearest Neighbor (DNN) method for constructing the undirected graph for segmentation. Compared to recent literature, this combination is over 35 times faster and achieves a coverability rate that is 65\% higher.",

author = "M.A.R. Pieck and \{Sommen, van der\}, F. and S. Zinger and \{With, de\}, P.H.N.",

year = "2015",

doi = "10.1109/ICIP.2015.7351390",

language = "English",

isbn = "978-1-4799-8339-1",

pages = "3180--3184",

booktitle = "Proceedings of the2015 IEEE International Conference on Image Processing (ICIP 2015), 27-30 September 2015, Quebec City, Canada",

publisher = "Institute of Electrical and Electronics Engineers",

address = "United States",

note = "22nd IEEE International Conference on Image Processing (ICIP 2015), ICIP 2015 ; Conference date: 27-09-2015 Through 30-09-2015",

url = "http://www.icip2015.org/",

}

Pieck, MAR, Sommen, van der, F , Zinger, S & With, de, PHN 2015, Real-time semantic context labeling for image understanding. in Proceedings of the2015 IEEE International Conference on Image Processing (ICIP 2015), 27-30 September 2015, Quebec City, Canada. Institute of Electrical and Electronics Engineers, Piscataway, blz. 3180-3184, 22nd IEEE International Conference on Image Processing (ICIP 2015), Quebec, Canada, 27/09/15. https://doi.org/10.1109/ICIP.2015.7351390

Real-time semantic context labeling for image understanding. / Pieck, M.A.R.; Sommen, van der, F.; Zinger, S. et al.
Proceedings of the2015 IEEE International Conference on Image Processing (ICIP 2015), 27-30 September 2015, Quebec City, Canada. Piscataway: Institute of Electrical and Electronics Engineers, 2015. blz. 3180-3184.

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review

TY - GEN

T1 - Real-time semantic context labeling for image understanding

AU - Pieck, M.A.R.

AU - Sommen, van der, F.

AU - Zinger, S.

AU - With, de, P.H.N.

N1 - Conference code: 22

PY - 2015

Y1 - 2015

N2 - The use of context information in a scene is an important aid for full semantic scene understanding in security and surveillance applications. To this end, this paper presents an innovative semantic context-labeling algorithm for three context classes, trading-off quality and real-time execution. Our system consists of three consecutive stages: image segmentation, region-based feature extraction and classification. We propose the joint use of the features color in HSV space, texture from Gabor filters and spatial context, in combination with the Directional Nearest Neighbor (DNN) method for constructing the undirected graph for segmentation. Compared to recent literature, this combination is over 35 times faster and achieves a coverability rate that is 65% higher.

AB - The use of context information in a scene is an important aid for full semantic scene understanding in security and surveillance applications. To this end, this paper presents an innovative semantic context-labeling algorithm for three context classes, trading-off quality and real-time execution. Our system consists of three consecutive stages: image segmentation, region-based feature extraction and classification. We propose the joint use of the features color in HSV space, texture from Gabor filters and spatial context, in combination with the Directional Nearest Neighbor (DNN) method for constructing the undirected graph for segmentation. Compared to recent literature, this combination is over 35 times faster and achieves a coverability rate that is 65% higher.

U2 - 10.1109/ICIP.2015.7351390

DO - 10.1109/ICIP.2015.7351390

M3 - Conference contribution

SN - 978-1-4799-8339-1

SP - 3180

EP - 3184

BT - Proceedings of the2015 IEEE International Conference on Image Processing (ICIP 2015), 27-30 September 2015, Quebec City, Canada

PB - Institute of Electrical and Electronics Engineers

CY - Piscataway

T2 - 22nd IEEE International Conference on Image Processing (ICIP 2015)

Y2 - 27 September 2015 through 30 September 2015

ER -

Real-time semantic context labeling for image understanding

Samenvatting

Congres

Toegang tot document

Vingerafdruk

Citeer dit