Multimodal feature fusion for video forgery detection

Girija Chetty, M Lipton

Research output: A Conference proceeding or a Chapter in BookConference contribution

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Abstract

In this paper we propose a novel local feature analysis and feature level fusion technique for detecting tampering or forgery for facial-biometric based on-line access control scenarios. The local features are extracted by analysing facial image data in the chrominance colour space and hue-saturation colour space. A feature level fusion of local features consisting of hue and saturation gradients with global features obtained from principal component analysis showed that a significant improvement in performance can be achieved in detecting tampered or forged images from genuine images in low bandwidth online streaming video access control contexts. The performance evaluation of the proposed fusion technique for a multimodal facial video corpus showed that an equal error rate of less than 1% could be achieved with feature level fusion of local features and global features.
Original languageEnglish
Title of host publicationProceedings of the 13th International Conference on Information Fusion
Place of PublicationPiscataway, N.J., USA
PublisherIEEE
ISBN (Print)9780982443811
Publication statusPublished - 2010
EventFusion 2010: 13th International Conference on Information Fusion - Edinburgh, United Kingdom
Duration: 26 Jul 201029 Jul 2010

Conference

ConferenceFusion 2010: 13th International Conference on Information Fusion
CountryUnited Kingdom
CityEdinburgh
Period26/07/1029/07/10

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Fusion reactions
Access control
Color
Video streaming
Biometrics
Principal component analysis
Bandwidth

Cite this

Chetty, G., & Lipton, M. (2010). Multimodal feature fusion for video forgery detection. In Proceedings of the 13th International Conference on Information Fusion Piscataway, N.J., USA: IEEE.
Chetty, Girija ; Lipton, M. / Multimodal feature fusion for video forgery detection. Proceedings of the 13th International Conference on Information Fusion. Piscataway, N.J., USA : IEEE, 2010.
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title = "Multimodal feature fusion for video forgery detection",
abstract = "In this paper we propose a novel local feature analysis and feature level fusion technique for detecting tampering or forgery for facial-biometric based on-line access control scenarios. The local features are extracted by analysing facial image data in the chrominance colour space and hue-saturation colour space. A feature level fusion of local features consisting of hue and saturation gradients with global features obtained from principal component analysis showed that a significant improvement in performance can be achieved in detecting tampered or forged images from genuine images in low bandwidth online streaming video access control contexts. The performance evaluation of the proposed fusion technique for a multimodal facial video corpus showed that an equal error rate of less than 1{\%} could be achieved with feature level fusion of local features and global features.",
author = "Girija Chetty and M Lipton",
year = "2010",
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Chetty, G & Lipton, M 2010, Multimodal feature fusion for video forgery detection. in Proceedings of the 13th International Conference on Information Fusion. IEEE, Piscataway, N.J., USA, Fusion 2010: 13th International Conference on Information Fusion, Edinburgh, United Kingdom, 26/07/10.

Multimodal feature fusion for video forgery detection. / Chetty, Girija; Lipton, M.

Proceedings of the 13th International Conference on Information Fusion. Piscataway, N.J., USA : IEEE, 2010.

Research output: A Conference proceeding or a Chapter in BookConference contribution

TY - GEN

T1 - Multimodal feature fusion for video forgery detection

AU - Chetty, Girija

AU - Lipton, M

PY - 2010

Y1 - 2010

N2 - In this paper we propose a novel local feature analysis and feature level fusion technique for detecting tampering or forgery for facial-biometric based on-line access control scenarios. The local features are extracted by analysing facial image data in the chrominance colour space and hue-saturation colour space. A feature level fusion of local features consisting of hue and saturation gradients with global features obtained from principal component analysis showed that a significant improvement in performance can be achieved in detecting tampered or forged images from genuine images in low bandwidth online streaming video access control contexts. The performance evaluation of the proposed fusion technique for a multimodal facial video corpus showed that an equal error rate of less than 1% could be achieved with feature level fusion of local features and global features.

AB - In this paper we propose a novel local feature analysis and feature level fusion technique for detecting tampering or forgery for facial-biometric based on-line access control scenarios. The local features are extracted by analysing facial image data in the chrominance colour space and hue-saturation colour space. A feature level fusion of local features consisting of hue and saturation gradients with global features obtained from principal component analysis showed that a significant improvement in performance can be achieved in detecting tampered or forged images from genuine images in low bandwidth online streaming video access control contexts. The performance evaluation of the proposed fusion technique for a multimodal facial video corpus showed that an equal error rate of less than 1% could be achieved with feature level fusion of local features and global features.

M3 - Conference contribution

SN - 9780982443811

BT - Proceedings of the 13th International Conference on Information Fusion

PB - IEEE

CY - Piscataway, N.J., USA

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Chetty G, Lipton M. Multimodal feature fusion for video forgery detection. In Proceedings of the 13th International Conference on Information Fusion. Piscataway, N.J., USA: IEEE. 2010