Facial image clustering in stereo videos using local binary patterns and double spectral analysis

Georgios Orfanidis; Anastasios Tefas; Nikos Nikolaidis; Ioannis Pitas

doi:10.1109/CIDM.2014.7008670

Facial image clustering in stereo videos using local binary patterns and double spectral analysis

Georgios Orfanidis, Anastasios Tefas, Nikos Nikolaidis, Ioannis Pitas

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

3 Citations (Scopus)

699 Downloads (Pure)

Abstract

In this work we proposed the use of local binary patterns in combination with double spectral analysis for facial image clustering applied to 3D (stereoscopic) videos. Double spectral clustering involves the fusion of two well known algorithms: Normalized cuts and spectral clustering in order to improve the clustering performance. The use of local binary patterns upon selected fiducial points on the facial images proved to be a good choice for describing images. The framework is applied on 3D videos and makes use of the additional information deriving from
the existence of two channels, left and right for further improving the clustering results.

Original language	English
Title of host publication	2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM 2014)
Subtitle of host publication	Proceedings of a meeting held 9-12 December 2014, Orlando, Florida, USA
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	217-221
Number of pages	5
ISBN (Electronic)	9781479945184
ISBN (Print)	9781479945177
DOIs	https://doi.org/10.1109/CIDM.2014.7008670
Publication status	Published - Mar 2015
Event	2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM 2014) - Orlando, FL, United States Duration: 9 Dec 2014 → 12 Dec 2014

Conference

Conference	2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM 2014)
Country/Territory	United States
City	Orlando, FL
Period	9/12/14 → 12/12/14

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10.1109/CIDM.2014.7008670

Ioannis Pitas - Facial Image Clustering in Stereo Videos Using Local Binary Patterns and Double Spectral Analysis - 2014
This is the author accepted manuscript (AAM). The final published version (version of record) is available online via IEEE at http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7008670. Please refer to any applicable terms of use of the publisher.
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Orfanidis, G., Tefas, A., Nikolaidis, N., & Pitas, I. (2015). Facial image clustering in stereo videos using local binary patterns and double spectral analysis. In 2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM 2014) : Proceedings of a meeting held 9-12 December 2014, Orlando, Florida, USA (pp. 217-221). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/CIDM.2014.7008670

Orfanidis, Georgios ; Tefas, Anastasios ; Nikolaidis, Nikos et al. / Facial image clustering in stereo videos using local binary patterns and double spectral analysis. 2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM 2014) : Proceedings of a meeting held 9-12 December 2014, Orlando, Florida, USA. Institute of Electrical and Electronics Engineers (IEEE), 2015. pp. 217-221

@inproceedings{2e64d80daf9141ccb194487dcdd067a0,

title = "Facial image clustering in stereo videos using local binary patterns and double spectral analysis",

abstract = "In this work we proposed the use of local binary patterns in combination with double spectral analysis for facial image clustering applied to 3D (stereoscopic) videos. Double spectral clustering involves the fusion of two well known algorithms: Normalized cuts and spectral clustering in order to improve the clustering performance. The use of local binary patterns upon selected fiducial points on the facial images proved to be a good choice for describing images. The framework is applied on 3D videos and makes use of the additional information deriving from the existence of two channels, left and right for further improving the clustering results.",

author = "Georgios Orfanidis and Anastasios Tefas and Nikos Nikolaidis and Ioannis Pitas",

year = "2015",

month = mar,

doi = "10.1109/CIDM.2014.7008670",

language = "English",

isbn = "9781479945177",

pages = "217--221",

booktitle = "2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM 2014)",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

address = "United States",

note = "2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM 2014) ; Conference date: 09-12-2014 Through 12-12-2014",

}

Orfanidis, G, Tefas, A, Nikolaidis, N & Pitas, I 2015, Facial image clustering in stereo videos using local binary patterns and double spectral analysis. in 2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM 2014) : Proceedings of a meeting held 9-12 December 2014, Orlando, Florida, USA. Institute of Electrical and Electronics Engineers (IEEE), pp. 217-221, 2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM 2014), Orlando, FL, United States, 9/12/14. https://doi.org/10.1109/CIDM.2014.7008670

Facial image clustering in stereo videos using local binary patterns and double spectral analysis. / Orfanidis, Georgios; Tefas, Anastasios; Nikolaidis, Nikos et al.
2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM 2014) : Proceedings of a meeting held 9-12 December 2014, Orlando, Florida, USA. Institute of Electrical and Electronics Engineers (IEEE), 2015. p. 217-221.

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

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AU - Pitas, Ioannis

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N2 - In this work we proposed the use of local binary patterns in combination with double spectral analysis for facial image clustering applied to 3D (stereoscopic) videos. Double spectral clustering involves the fusion of two well known algorithms: Normalized cuts and spectral clustering in order to improve the clustering performance. The use of local binary patterns upon selected fiducial points on the facial images proved to be a good choice for describing images. The framework is applied on 3D videos and makes use of the additional information deriving from the existence of two channels, left and right for further improving the clustering results.

AB - In this work we proposed the use of local binary patterns in combination with double spectral analysis for facial image clustering applied to 3D (stereoscopic) videos. Double spectral clustering involves the fusion of two well known algorithms: Normalized cuts and spectral clustering in order to improve the clustering performance. The use of local binary patterns upon selected fiducial points on the facial images proved to be a good choice for describing images. The framework is applied on 3D videos and makes use of the additional information deriving from the existence of two channels, left and right for further improving the clustering results.

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DO - 10.1109/CIDM.2014.7008670

M3 - Conference Contribution (Conference Proceeding)

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BT - 2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM 2014)

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Orfanidis G, Tefas A, Nikolaidis N, Pitas I. Facial image clustering in stereo videos using local binary patterns and double spectral analysis. In 2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM 2014) : Proceedings of a meeting held 9-12 December 2014, Orlando, Florida, USA. Institute of Electrical and Electronics Engineers (IEEE). 2015. p. 217-221 Epub 2015 Jan 15. doi: 10.1109/CIDM.2014.7008670

Facial image clustering in stereo videos using local binary patterns and double spectral analysis

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