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Mood Recognition Based on Upper Body Posture and Movement Features

  • Conference paper

Part of the Lecture Notes in Computer Science book series (LNIP,volume 6974)

Abstract

While studying body postures in relation to mood is not a new concept, the majority of these studies rely on actors interpretations. This project investigated the temporal aspects of naturalistic body postures while users listened to mood inducing music. Video data was collected while participants listened to eight minutes of music during two sessions (happy and sad) in a within-subjects design. Subjectively reported mood scores validated that mood did differ significantly for valence and energy. Video analysis consisted of postural ratings for the head, shoulders, trunk, arms, and head and hand tapping. Results showed significant differences for the majority of these dimensions by mood. This study showed that certain body postures are indicative of certain mood states in a naturalistic setting.

Keywords

  • Affective body posture/movement
  • emotion recognition
  • body posture coding

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© 2011 Springer-Verlag Berlin Heidelberg

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Thrasher, M., Van der Zwaag, M.D., Bianchi-Berthouze, N., Westerink, J.H.D.M. (2011). Mood Recognition Based on Upper Body Posture and Movement Features. In: D’Mello, S., Graesser, A., Schuller, B., Martin, JC. (eds) Affective Computing and Intelligent Interaction. ACII 2011. Lecture Notes in Computer Science, vol 6974. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24600-5_41

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  • DOI: https://doi.org/10.1007/978-3-642-24600-5_41

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-24599-2

  • Online ISBN: 978-3-642-24600-5

  • eBook Packages: Computer ScienceComputer Science (R0)