Semi-supervised dimensionality reduction on data with multiple representations for label propagation on facial images

Olga Zoidi; Nikos Nikolaidis; Ioannis Pitas

doi:10.1109/ICASSP.2014.6854759

Semi-supervised dimensionality reduction on data with multiple representations for label propagation on facial images

Olga Zoidi, Nikos Nikolaidis, Ioannis Pitas

Department of Electrical & Electronic Engineering

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

4 Citations (Scopus)

299 Downloads (Pure)

Abstract

In this paper a novel method is introduced for semi-supervised dimensionality reduction on facial images extracted from stereo videos. It operates on image data with multiple representations and calculates a projection matrix that preserves locality information and a priori pairwise information, in the form of must-link and cannot-link constraints between the various data representations, as well as label information for a percentage of the data. The final data representation is a linear combination of the projections of all data representations. The performance of the proposed Semi-supervised Multiple
Locality Preserving Projections method was evaluated in person identity label propagation on facial images extracted from stereo movies. Experimental results showed that the proposed method outperforms state of the art methods.

Original language	English
Title of host publication	2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2014)
Subtitle of host publication	Proceedings of a meeting held 4-9 May 2014, Florence, Italy
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	6019-6023
Number of pages	5
ISBN (Electronic)	9781479928927
ISBN (Print)	9781479928941
DOIs	https://doi.org/10.1109/ICASSP.2014.6854759
Publication status	Published - Sept 2014
Event	2014 IEEE International Conference on Acoustics, Speech and Signal Processing - Florence, Italy Duration: 4 May 2014 → 9 May 2014

Publication series

Name	Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
ISSN (Print)	1520-6149

Conference

Conference	2014 IEEE International Conference on Acoustics, Speech and Signal Processing
Abbreviated title	ICASSP '14
Country/Territory	Italy
City	Florence
Period	4/05/14 → 9/05/14

Keywords

Locality preserving projections
semi-supervised learning
label propagation

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10.1109/ICASSP.2014.6854759

Ioannis Pitas - Semi-Supervised Dimensionality Reduction on Data with Multiple Representations for Label Propagation on Facial Images
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=6854759. Please refer to any applicable terms of use of the publisher.
Accepted author manuscript, 234 KB

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Zoidi, O., Nikolaidis, N., & Pitas, I. (2014). Semi-supervised dimensionality reduction on data with multiple representations for label propagation on facial images. In 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2014): Proceedings of a meeting held 4-9 May 2014, Florence, Italy (pp. 6019-6023). (Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/ICASSP.2014.6854759

Zoidi, Olga ; Nikolaidis, Nikos ; Pitas, Ioannis. / Semi-supervised dimensionality reduction on data with multiple representations for label propagation on facial images. 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2014): Proceedings of a meeting held 4-9 May 2014, Florence, Italy. Institute of Electrical and Electronics Engineers (IEEE), 2014. pp. 6019-6023 (Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)).

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title = "Semi-supervised dimensionality reduction on data with multiple representations for label propagation on facial images",

abstract = "In this paper a novel method is introduced for semi-supervised dimensionality reduction on facial images extracted from stereo videos. It operates on image data with multiple representations and calculates a projection matrix that preserves locality information and a priori pairwise information, in the form of must-link and cannot-link constraints between the various data representations, as well as label information for a percentage of the data. The final data representation is a linear combination of the projections of all data representations. The performance of the proposed Semi-supervised MultipleLocality Preserving Projections method was evaluated in person identity label propagation on facial images extracted from stereo movies. Experimental results showed that the proposed method outperforms state of the art methods.",

keywords = "Locality preserving projections, semi-supervised learning, label propagation",

author = "Olga Zoidi and Nikos Nikolaidis and Ioannis Pitas",

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booktitle = "2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2014)",

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Zoidi, O, Nikolaidis, N & Pitas, I 2014, Semi-supervised dimensionality reduction on data with multiple representations for label propagation on facial images. in 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2014): Proceedings of a meeting held 4-9 May 2014, Florence, Italy. Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Institute of Electrical and Electronics Engineers (IEEE), pp. 6019-6023, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing, Florence, Italy, 4/05/14. https://doi.org/10.1109/ICASSP.2014.6854759

Semi-supervised dimensionality reduction on data with multiple representations for label propagation on facial images. / Zoidi, Olga; Nikolaidis, Nikos; Pitas, Ioannis.
2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2014): Proceedings of a meeting held 4-9 May 2014, Florence, Italy. Institute of Electrical and Electronics Engineers (IEEE), 2014. p. 6019-6023 (Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)).

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

TY - GEN

T1 - Semi-supervised dimensionality reduction on data with multiple representations for label propagation on facial images

AU - Zoidi, Olga

AU - Nikolaidis, Nikos

AU - Pitas, Ioannis

PY - 2014/9

Y1 - 2014/9

N2 - In this paper a novel method is introduced for semi-supervised dimensionality reduction on facial images extracted from stereo videos. It operates on image data with multiple representations and calculates a projection matrix that preserves locality information and a priori pairwise information, in the form of must-link and cannot-link constraints between the various data representations, as well as label information for a percentage of the data. The final data representation is a linear combination of the projections of all data representations. The performance of the proposed Semi-supervised MultipleLocality Preserving Projections method was evaluated in person identity label propagation on facial images extracted from stereo movies. Experimental results showed that the proposed method outperforms state of the art methods.

AB - In this paper a novel method is introduced for semi-supervised dimensionality reduction on facial images extracted from stereo videos. It operates on image data with multiple representations and calculates a projection matrix that preserves locality information and a priori pairwise information, in the form of must-link and cannot-link constraints between the various data representations, as well as label information for a percentage of the data. The final data representation is a linear combination of the projections of all data representations. The performance of the proposed Semi-supervised MultipleLocality Preserving Projections method was evaluated in person identity label propagation on facial images extracted from stereo movies. Experimental results showed that the proposed method outperforms state of the art methods.

KW - Locality preserving projections

KW - semi-supervised learning

KW - label propagation

U2 - 10.1109/ICASSP.2014.6854759

DO - 10.1109/ICASSP.2014.6854759

M3 - Conference Contribution (Conference Proceeding)

SN - 9781479928941

T3 - Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

SP - 6019

EP - 6023

BT - 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2014)

PB - Institute of Electrical and Electronics Engineers (IEEE)

T2 - 2014 IEEE International Conference on Acoustics, Speech and Signal Processing

Y2 - 4 May 2014 through 9 May 2014

ER -

Zoidi O, Nikolaidis N, Pitas I. Semi-supervised dimensionality reduction on data with multiple representations for label propagation on facial images. In 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2014): Proceedings of a meeting held 4-9 May 2014, Florence, Italy. Institute of Electrical and Electronics Engineers (IEEE). 2014. p. 6019-6023. (Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)). doi: 10.1109/ICASSP.2014.6854759

Semi-supervised dimensionality reduction on data with multiple representations for label propagation on facial images

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