Thermal Super-Pixels for Bimodal Stress Recognition

Ramin Irani, Kamal Nasrollahi, Abhinav Dhall, Thomas B. Moeslund, Tom Gedeon

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

5 Citations (Scopus)
283 Downloads (Pure)

Abstract

Stress is a response to time pressure or negative environmental conditions. If its stimulus iterates or stays for a long time, it affects health conditions. Thus, stress recognition is an important issue. Traditional systems for this purpose are mostly contact-based, i.e., they require a sensor to be in touch with the body which is not always practical. Contact-free monitoring of the stress by a camera [1, 2] can be an alternative. These systems usually utilize only an RGB or a thermal camera to recognize stress. To the best of our knowledge, the only work on fusion of these two modalities for stress recognition is [3] which uses a feature level fusion of the two modalities. The features in [3] are extracted directly from pixel values. In this paper we show that extracting the features from super-pixels, followed by decision level fusion results in a system outperforming [3]. The experimental results on ANUstressDB database show that our system achieves 89% classification accuracy.
Original languageEnglish
Title of host publicationIEEE International Conference on Image Processing Theory, Tools and Applications
PublisherIEEE
Publication dateDec 2016
ISBN (Print)978-1-4673-8911-2
ISBN (Electronic)978-1-4673-8910-5
DOIs
Publication statusPublished - Dec 2016
EventIEEE International Conference on Image Processing Theory, Tools and Applications - Oulu, Finland
Duration: 12 Dec 201615 Dec 2016
Conference number: 6
http://www.ipta-conference.com/ipta16/

Conference

ConferenceIEEE International Conference on Image Processing Theory, Tools and Applications
Number6
CountryFinland
CityOulu
Period12/12/201615/12/2016
Internet address

Fingerprint

Pixels
Fusion reactions
Cameras
Hot Temperature
Health
Monitoring
Sensors

Keywords

  • Stress Recognition
  • Facial Expression
  • RGB Images
  • Thermal Images
  • super-pixels

Cite this

Irani, R., Nasrollahi, K., Dhall, A., Moeslund, T. B., & Gedeon, T. (2016). Thermal Super-Pixels for Bimodal Stress Recognition. In IEEE International Conference on Image Processing Theory, Tools and Applications IEEE. https://doi.org/10.1109/IPTA.2016.7821002
Irani, Ramin ; Nasrollahi, Kamal ; Dhall, Abhinav ; Moeslund, Thomas B. ; Gedeon, Tom. / Thermal Super-Pixels for Bimodal Stress Recognition. IEEE International Conference on Image Processing Theory, Tools and Applications. IEEE, 2016.
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Irani, R, Nasrollahi, K, Dhall, A, Moeslund, TB & Gedeon, T 2016, Thermal Super-Pixels for Bimodal Stress Recognition. in IEEE International Conference on Image Processing Theory, Tools and Applications. IEEE, IEEE International Conference on Image Processing Theory, Tools and Applications, Oulu, Finland, 12/12/2016. https://doi.org/10.1109/IPTA.2016.7821002

Thermal Super-Pixels for Bimodal Stress Recognition. / Irani, Ramin; Nasrollahi, Kamal; Dhall, Abhinav; Moeslund, Thomas B.; Gedeon, Tom.

IEEE International Conference on Image Processing Theory, Tools and Applications. IEEE, 2016.

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

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Irani R, Nasrollahi K, Dhall A, Moeslund TB, Gedeon T. Thermal Super-Pixels for Bimodal Stress Recognition. In IEEE International Conference on Image Processing Theory, Tools and Applications. IEEE. 2016 https://doi.org/10.1109/IPTA.2016.7821002