Affective gait recognition and baseline evaluation from real world samples

Vili Kellokumpu (Corresponding author), Markus Särkiniemi, Guoying Zhao

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

1 Citation (Scopus)


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 languageEnglish
Title of host publicationComputer Vision - ACCV 2016 Workshops
Subtitle of host publicationACCV 2016 International Workshops
EditorsJiwen Lu, Kai-Kuang Ma, Chu-Song Chen
Number of pages9
ISBN (Electronic)978-3-319-54407-6
ISBN (Print)978-3-319-54406-9
Publication statusPublished - 1 Jan 2017
MoE publication typeA4 Article in a conference publication
Event13th Asian Conference on Computer Vision, ACCV 2016 - Taipei, Taiwan, Province of China
Duration: 20 Nov 201624 Nov 2016

Publication series

SeriesLecture Notes in Computer Science


Conference13th Asian Conference on Computer Vision, ACCV 2016
Country/TerritoryTaiwan, Province of China
City Taipei


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