Heuristic method of feature selection for person re-identification based on gait motion capture data

Henryk Josiński; Agnieszka Michalczuk; Daniel Kostrzewa; Adam Świtoński; Konrad Wojciechowski

doi:10.1007/978-3-319-05458-2_60

Heuristic method of feature selection for person re-identification based on gait motion capture data

Polish-Japanese Academy of Information Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

5 Citations (Scopus)

Abstract

The authors present a heuristic method of feature selection for gait mocap data, based on the exIWO metaheuristic which is characterized by both the hybrid strategy of the search space exploration and three variants of selection of individuals as candidates for next population. The proposed method was evaluated by the accuracy of person re-identification based on the selected feature subset. Because of the high-dimensional nature of motion data, feature selection was preceded by the data dimensionality reduction.

Original language	English
Title of host publication	Intelligent Information and Database Systems - 6th Asian Conference, ACIIDS 2014, Proceedings
Publisher	Springer Verlag
Pages	585-594
Number of pages	10
Edition	PART 2
ISBN (Print)	9783319054575
DOIs	https://doi.org/10.1007/978-3-319-05458-2_60
Publication status	Published - 2014
Event	6th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2014 - Bangkok, Thailand Duration: 7 Apr 2014 → 9 Apr 2014

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 2
Volume	8398 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	6th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2014
Country/Territory	Thailand
City	Bangkok
Period	7/04/14 → 9/04/14

Keywords

MPCA algorithm
dimensionality reduction
exIWO algorithm
feature selection
gait analysis
person re-identification

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-319-05458-2_60

Cite this

Josiński, H., Michalczuk, A., Kostrzewa, D., Świtoński, A., & Wojciechowski, K. (2014). Heuristic method of feature selection for person re-identification based on gait motion capture data. In Intelligent Information and Database Systems - 6th Asian Conference, ACIIDS 2014, Proceedings (PART 2 ed., pp. 585-594). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8398 LNAI, No. PART 2). Springer Verlag. https://doi.org/10.1007/978-3-319-05458-2_60

Josiński, Henryk ; Michalczuk, Agnieszka ; Kostrzewa, Daniel et al. / Heuristic method of feature selection for person re-identification based on gait motion capture data. Intelligent Information and Database Systems - 6th Asian Conference, ACIIDS 2014, Proceedings. PART 2. ed. Springer Verlag, 2014. pp. 585-594 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2).

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title = "Heuristic method of feature selection for person re-identification based on gait motion capture data",

abstract = "The authors present a heuristic method of feature selection for gait mocap data, based on the exIWO metaheuristic which is characterized by both the hybrid strategy of the search space exploration and three variants of selection of individuals as candidates for next population. The proposed method was evaluated by the accuracy of person re-identification based on the selected feature subset. Because of the high-dimensional nature of motion data, feature selection was preceded by the data dimensionality reduction.",

keywords = "MPCA algorithm, dimensionality reduction, exIWO algorithm, feature selection, gait analysis, person re-identification",

author = "Henryk Josi{\'n}ski and Agnieszka Michalczuk and Daniel Kostrzewa and Adam {\'S}wito{\'n}ski and Konrad Wojciechowski",

year = "2014",

doi = "10.1007/978-3-319-05458-2\_60",

language = "English",

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series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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booktitle = "Intelligent Information and Database Systems - 6th Asian Conference, ACIIDS 2014, Proceedings",

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note = "6th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2014 ; Conference date: 07-04-2014 Through 09-04-2014",

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Josiński, H , Michalczuk, A , Kostrzewa, D , Świtoński, A & Wojciechowski, K 2014, Heuristic method of feature selection for person re-identification based on gait motion capture data. in Intelligent Information and Database Systems - 6th Asian Conference, ACIIDS 2014, Proceedings. PART 2 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 2, vol. 8398 LNAI, Springer Verlag, pp. 585-594, 6th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2014, Bangkok, Thailand, 7/04/14. https://doi.org/10.1007/978-3-319-05458-2_60

Heuristic method of feature selection for person re-identification based on gait motion capture data. / Josiński, Henryk ; Michalczuk, Agnieszka ; Kostrzewa, Daniel et al.
Intelligent Information and Database Systems - 6th Asian Conference, ACIIDS 2014, Proceedings. PART 2. ed. Springer Verlag, 2014. p. 585-594 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8398 LNAI, No. PART 2).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Heuristic method of feature selection for person re-identification based on gait motion capture data

AU - Josiński, Henryk

AU - Michalczuk, Agnieszka

AU - Kostrzewa, Daniel

AU - Świtoński, Adam

AU - Wojciechowski, Konrad

PY - 2014

Y1 - 2014

N2 - The authors present a heuristic method of feature selection for gait mocap data, based on the exIWO metaheuristic which is characterized by both the hybrid strategy of the search space exploration and three variants of selection of individuals as candidates for next population. The proposed method was evaluated by the accuracy of person re-identification based on the selected feature subset. Because of the high-dimensional nature of motion data, feature selection was preceded by the data dimensionality reduction.

AB - The authors present a heuristic method of feature selection for gait mocap data, based on the exIWO metaheuristic which is characterized by both the hybrid strategy of the search space exploration and three variants of selection of individuals as candidates for next population. The proposed method was evaluated by the accuracy of person re-identification based on the selected feature subset. Because of the high-dimensional nature of motion data, feature selection was preceded by the data dimensionality reduction.

KW - MPCA algorithm

KW - dimensionality reduction

KW - exIWO algorithm

KW - feature selection

KW - gait analysis

KW - person re-identification

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U2 - 10.1007/978-3-319-05458-2_60

DO - 10.1007/978-3-319-05458-2_60

M3 - Conference contribution

AN - SCOPUS:84958528734

SN - 9783319054575

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 585

EP - 594

BT - Intelligent Information and Database Systems - 6th Asian Conference, ACIIDS 2014, Proceedings

PB - Springer Verlag

T2 - 6th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2014

Y2 - 7 April 2014 through 9 April 2014

ER -

Josiński H , Michalczuk A , Kostrzewa D , Świtoński A, Wojciechowski K. Heuristic method of feature selection for person re-identification based on gait motion capture data. In Intelligent Information and Database Systems - 6th Asian Conference, ACIIDS 2014, Proceedings. PART 2 ed. Springer Verlag. 2014. p. 585-594. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2). doi: 10.1007/978-3-319-05458-2_60

Heuristic method of feature selection for person re-identification based on gait motion capture data

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

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