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Cited by 88Emotion and Mood RecognitionSoftware Engineering Techniques and PracticesGaze Tracking and Assistive Technology

The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.

Emotion recognition and its application in software engineering

Kolakowska, Agata, Landowska, Agnieszka, Szwoch, Mariusz, Szwoch, Wioleta, Wrobel, Michal R.·2013·2013 6th International Conference on Human System Interactions (HSI)
DOI 10.1109/hsi.2013.6577877
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Abstract

In this paper a novel application of multimodal emotion recognition algorithms in software engineering is described. Several application scenarios are proposed concerning program usability testing and software process improvement. Also a set of emotional states relevant in that application area is identified. The multimodal emotion recognition method that integrates video and depth channels, physiological signals and input devices usage patterns is proposed and some preliminary results on learning set creation are described.

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Research works printed but not linked: 42

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Metadata

Authors
Kolakowska, A., Landowska, A., Szwoch, M., Szwoch, W., & Wrobel, M. R.
Affiliations
Gdańsk University of Technology (PL)
ORCID
Venue
2013 6th International Conference on Human System Interactions (HSI)
Publisher
IEEE
Published
2013-06
Pages
532-539
DOI
10.1109/hsi.2013.6577877
OpenAlex
W2046005471
Cited by
88
References
7
Citations by year
2026: 4 · 2025: 4 · 2024: 3 · 2023: 11 · 2022: 6 · 2021: 11 · 2020: 8 · 2019: 7 · 2018: 9 · 2017: 5 · 2016: 6 · 2015: 10 · 2014: 4
FWCI
4.53
Type
conference paper
Language
en
Open access
closed
Locations
Conference on Human System Interactions (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Emotion and Mood Recognition
  • Physical Sciences › Computer Science › Information Systems › Software Engineering Techniques and Practices
  • Physical Sciences › Computer Science › Human-Computer Interaction › Gaze Tracking and Assistive Technology
Keywords
multimodal emotion recognition, software engineering, software process improvement, emotional state, physiological signals

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