Affective gait recognition and baseline evaluation from real world samples

Vili Kellokumpu; Markus Särkiniemi; Guoying Zhao

doi:10.1007/978-3-319-54407-6_38

Affective gait recognition and baseline evaluation from real world samples

Vili Kellokumpu^*
, Markus Särkiniemi
, Guoying Zhao

^*Corresponding author for this work

Not published at VTT

University of Oulu

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

4 Citations (Scopus)

Abstract

Over the years a lot of research efforts have been put into recognizing human emotions from facial expressions. However, in many scenarios access to suitable face data is difficult, and therefore there is a need for methodology that can be used when people are observed from a distance. A potential modality for this is human gait. Early attempts to recognize human emotion from gait have been limited to acted data. Furthermore, in these approaches the data has been captured in controlled settings. This paper presents the first experiments for automated affective gait recognition using non acted real world samples. A database of 96 subjects affected by positive or negative feedback is collected and two baseline methods are used to recognize the affective state of a person. The baseline results are promising and encourage further study in this domain.

Original language	English
Title of host publication	Computer Vision - ACCV 2016 Workshops
Subtitle of host publication	ACCV 2016 International Workshops
Editors	Chu-Song Chen, Jiwen Lu, Kai-Kuang Ma
Publisher	Springer
Pages	567-575
ISBN (Electronic)	978-3-319-54407-6
ISBN (Print)	978-3-319-54406-9
DOIs	https://doi.org/10.1007/978-3-319-54407-6_38
Publication status	Published - 1 Jan 2017
MoE publication type	A4 Article in a conference publication
Event	13th Asian Conference on Computer Vision, ACCV 2016 - Taipei, Taiwan, Province of China Duration: 20 Nov 2016 → 24 Nov 2016

Publication series

Series	Lecture Notes in Computer Science
Volume	10116
ISSN	0302-9743

Conference

Conference	13th Asian Conference on Computer Vision, ACCV 2016
Country/Territory	Taiwan, Province of China
City	Taipei
Period	20/11/16 → 24/11/16

Funding

This work was sponsored by the Academy of Finland, Infotech Oulu and Nokia Visiting Professor grant.

Access to Document

10.1007/978-3-319-54407-6_38

Cite this

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title = "Affective gait recognition and baseline evaluation from real world samples",

abstract = "Over the years a lot of research efforts have been put into recognizing human emotions from facial expressions. However, in many scenarios access to suitable face data is difficult, and therefore there is a need for methodology that can be used when people are observed from a distance. A potential modality for this is human gait. Early attempts to recognize human emotion from gait have been limited to acted data. Furthermore, in these approaches the data has been captured in controlled settings. This paper presents the first experiments for automated affective gait recognition using non acted real world samples. A database of 96 subjects affected by positive or negative feedback is collected and two baseline methods are used to recognize the affective state of a person. The baseline results are promising and encourage further study in this domain.",

author = "Vili Kellokumpu and Markus S{\"a}rkiniemi and Guoying Zhao",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2017.; 13th Asian Conference on Computer Vision, ACCV 2016 ; Conference date: 20-11-2016 Through 24-11-2016",

year = "2017",

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doi = "10.1007/978-3-319-54407-6\_38",

language = "English",

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series = "Lecture Notes in Computer Science",

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}

Kellokumpu, V, Särkiniemi, M & Zhao, G 2017, Affective gait recognition and baseline evaluation from real world samples. in C-S Chen, J Lu & K-K Ma (eds), Computer Vision - ACCV 2016 Workshops: ACCV 2016 International Workshops. Springer, Lecture Notes in Computer Science, vol. 10116, pp. 567-575, 13th Asian Conference on Computer Vision, ACCV 2016, Taipei, Taiwan, Province of China, 20/11/16. https://doi.org/10.1007/978-3-319-54407-6_38

Affective gait recognition and baseline evaluation from real world samples. / Kellokumpu, Vili; Särkiniemi, Markus; Zhao, Guoying.
Computer Vision - ACCV 2016 Workshops: ACCV 2016 International Workshops. ed. / Chu-Song Chen; Jiwen Lu; Kai-Kuang Ma. Springer, 2017. p. 567-575 (Lecture Notes in Computer Science, Vol. 10116).

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

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AU - Särkiniemi, Markus

AU - Zhao, Guoying

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N2 - Over the years a lot of research efforts have been put into recognizing human emotions from facial expressions. However, in many scenarios access to suitable face data is difficult, and therefore there is a need for methodology that can be used when people are observed from a distance. A potential modality for this is human gait. Early attempts to recognize human emotion from gait have been limited to acted data. Furthermore, in these approaches the data has been captured in controlled settings. This paper presents the first experiments for automated affective gait recognition using non acted real world samples. A database of 96 subjects affected by positive or negative feedback is collected and two baseline methods are used to recognize the affective state of a person. The baseline results are promising and encourage further study in this domain.

AB - Over the years a lot of research efforts have been put into recognizing human emotions from facial expressions. However, in many scenarios access to suitable face data is difficult, and therefore there is a need for methodology that can be used when people are observed from a distance. A potential modality for this is human gait. Early attempts to recognize human emotion from gait have been limited to acted data. Furthermore, in these approaches the data has been captured in controlled settings. This paper presents the first experiments for automated affective gait recognition using non acted real world samples. A database of 96 subjects affected by positive or negative feedback is collected and two baseline methods are used to recognize the affective state of a person. The baseline results are promising and encourage further study in this domain.

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Y2 - 20 November 2016 through 24 November 2016

ER -

Affective gait recognition and baseline evaluation from real world samples

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