Label propagation on data with multiple representations through multi-graph locality preserving projections

Olga Zoidi; Nikos Nikolaidis; Ioannis Pitas

Label propagation on data with multiple representations through multi-graph locality preserving projections

Olga Zoidi, Nikos Nikolaidis, Ioannis Pitas

Department of Electrical & Electronic Engineering

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

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Abstract

In this paper a novel method is introduced for propagating label information on data with multiple representations. The method performs dimensionality reduction of the data by calculating 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. The final data representations are then fused, in order to perform label propagation. The performance of the proposed method was evaluated on facial images extracted from stereo movies and on the UCF11 action recognition database. 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 Image Processing (ICIP 2014)
Subtitle of host publication	Proceedings of a meeting held 27-30 October 2014, Paris, France
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	1505-1509
Number of pages	5
ISBN (Electronic)	9781479957514
ISBN (Print)	9781479957521
Publication status	Published - Mar 2015
Event	IEEE International Conference on Image Processing (ICIP) - Paris, France Duration: 27 Oct 2014 → 30 Oct 2014

Publication series

Name	IEEE International Conference on Image Processing (ICIP)
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
ISSN (Print)	1522-4880

Conference

Conference	IEEE International Conference on Image Processing (ICIP)
Country/Territory	France
City	Paris
Period	27/10/14 → 30/10/14

Keywords

Locality preserving projections
dimensionality reduction
label propagation
multiple graphs

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Ioannis Pitas - Label Propagagion on Data with Multiple Representations Through Multi-graph Locality Preserving Projections - 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/xpls/abs_all.jsp?arnumber=7025301. Please refer to any applicable terms of use of the publisher.
Accepted author manuscript, 96.4 KB

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Zoidi, O., Nikolaidis, N., & Pitas, I. (2015). Label propagation on data with multiple representations through multi-graph locality preserving projections. In 2014 IEEE International Conference on Image Processing (ICIP 2014): Proceedings of a meeting held 27-30 October 2014, Paris, France (pp. 1505-1509). (IEEE International Conference on Image Processing (ICIP) ). Institute of Electrical and Electronics Engineers (IEEE).

Zoidi, Olga ; Nikolaidis, Nikos ; Pitas, Ioannis. / Label propagation on data with multiple representations through multi-graph locality preserving projections. 2014 IEEE International Conference on Image Processing (ICIP 2014): Proceedings of a meeting held 27-30 October 2014, Paris, France. Institute of Electrical and Electronics Engineers (IEEE), 2015. pp. 1505-1509 (IEEE International Conference on Image Processing (ICIP) ).

@inproceedings{df33518aeba446e0a56be19724b2de74,

title = "Label propagation on data with multiple representations through multi-graph locality preserving projections",

abstract = "In this paper a novel method is introduced for propagating label information on data with multiple representations. The method performs dimensionality reduction of the data by calculating a projection matrix that preserves localityinformation and a priori pairwise information, in the form of must-link and cannot-link constraints between the various data representations. The final data representations are then fused, in order to perform label propagation. The performance of the proposed method was evaluated on facial images extracted from stereo movies and on the UCF11 action recognition database. Experimental results showed that the proposed method outperforms state of the art methods.",

keywords = "Locality preserving projections, dimensionality reduction, label propagation, multiple graphs",

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

year = "2015",

month = mar,

language = "English",

isbn = "9781479957521",

series = "IEEE International Conference on Image Processing (ICIP) ",

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

pages = "1505--1509",

booktitle = "2014 IEEE International Conference on Image Processing (ICIP 2014)",

address = "United States",

note = "IEEE International Conference on Image Processing (ICIP) ; Conference date: 27-10-2014 Through 30-10-2014",

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Zoidi, O, Nikolaidis, N & Pitas, I 2015, Label propagation on data with multiple representations through multi-graph locality preserving projections. in 2014 IEEE International Conference on Image Processing (ICIP 2014): Proceedings of a meeting held 27-30 October 2014, Paris, France. IEEE International Conference on Image Processing (ICIP) , Institute of Electrical and Electronics Engineers (IEEE), pp. 1505-1509, IEEE International Conference on Image Processing (ICIP), Paris, France, 27/10/14.

Label propagation on data with multiple representations through multi-graph locality preserving projections. / Zoidi, Olga; Nikolaidis, Nikos; Pitas, Ioannis.
2014 IEEE International Conference on Image Processing (ICIP 2014): Proceedings of a meeting held 27-30 October 2014, Paris, France. Institute of Electrical and Electronics Engineers (IEEE), 2015. p. 1505-1509 (IEEE International Conference on Image Processing (ICIP) ).

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

TY - GEN

T1 - Label propagation on data with multiple representations through multi-graph locality preserving projections

AU - Zoidi, Olga

AU - Nikolaidis, Nikos

AU - Pitas, Ioannis

PY - 2015/3

Y1 - 2015/3

N2 - In this paper a novel method is introduced for propagating label information on data with multiple representations. The method performs dimensionality reduction of the data by calculating a projection matrix that preserves localityinformation and a priori pairwise information, in the form of must-link and cannot-link constraints between the various data representations. The final data representations are then fused, in order to perform label propagation. The performance of the proposed method was evaluated on facial images extracted from stereo movies and on the UCF11 action recognition database. Experimental results showed that the proposed method outperforms state of the art methods.

AB - In this paper a novel method is introduced for propagating label information on data with multiple representations. The method performs dimensionality reduction of the data by calculating a projection matrix that preserves localityinformation and a priori pairwise information, in the form of must-link and cannot-link constraints between the various data representations. The final data representations are then fused, in order to perform label propagation. The performance of the proposed method was evaluated on facial images extracted from stereo movies and on the UCF11 action recognition database. Experimental results showed that the proposed method outperforms state of the art methods.

KW - Locality preserving projections

KW - dimensionality reduction

KW - label propagation

KW - multiple graphs

M3 - Conference Contribution (Conference Proceeding)

SN - 9781479957521

T3 - IEEE International Conference on Image Processing (ICIP)

SP - 1505

EP - 1509

BT - 2014 IEEE International Conference on Image Processing (ICIP 2014)

PB - Institute of Electrical and Electronics Engineers (IEEE)

T2 - IEEE International Conference on Image Processing (ICIP)

Y2 - 27 October 2014 through 30 October 2014

ER -

Zoidi O, Nikolaidis N, Pitas I. Label propagation on data with multiple representations through multi-graph locality preserving projections. In 2014 IEEE International Conference on Image Processing (ICIP 2014): Proceedings of a meeting held 27-30 October 2014, Paris, France. Institute of Electrical and Electronics Engineers (IEEE). 2015. p. 1505-1509. (IEEE International Conference on Image Processing (ICIP) ). Epub 2014 Oct 27.

Label propagation on data with multiple representations through multi-graph locality preserving projections

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