Emotion Recognition by Body Movement Representation on the Manifold of Symmetric Positive Definite Matrices

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Daoudi, Mohamed; Berretti, Stefano; Pala, Pietro; Delevoye, Yvonne,; Bimbo, Alberto,;
  • Publisher: HAL CCSD
  • Related identifiers: doi: 10.1007/978-3-319-68560-1_49
  • Subject: [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV] | [SCCO.PSYC]Cognitive science/Psychology | [SCCO.NEUR]Cognitive science/Neuroscience | [ SCCO.PSYC ] Cognitive science/Psychology | Computer Science - Computer Vision and Pattern Recognition | [ SCCO.NEUR ] Cognitive science/Neuroscience | [ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]

International audience; Emotion recognition is attracting great interest for its potential application in a multitude of real-life situations. Much of the Computer Vision research in this field has focused on relating emotions to facial expressions, with investigations ... View more
  • References (19)
    19 references, page 1 of 2

    1. Arsigny, V., Fillard, P., Pennec, X., Ayache, N.: Geometric means in a novel vector space structure on symmetric positive-de nite matrices. SIAM Journal on Matrix Analysis and Applications 29(1), 328{347 (2007)

    2. Bhatia, R.: Positive De nite Matrices. Princeton University Press (2007)

    3. Bhattacharya, S., Kalayeh, M.M., Sukthankar, R., Shah, M.: Recognition of complex events: Exploiting temporal dynamics between underlying concepts. In: IEEE Conf. on Computer Vision and Pattern Recognition (CVPR). pp. 2243{2250 (2014)

    4. Bhattacharya, S., Souly, N., Shah, M.: Covariance of Motion and Appearance Features for Spatio Temporal Recognition Tasks. ArXiv e-prints (Jun 2016)

    5. Faraki, M., Harandi, M.T., Porikli, F.: Image set classi cation by symmetric positive semi-de nite matrices. In: IEEE Winter Conf. on Applications of Computer Vision (WACV). pp. 1{8 (2016)

    6. Gong, L., Wang, T., Wang, C., Liu, F., Zhang, F., Yu, X.: Recognizing a ect from non-stylized body motion using shape of gaussian descriptors. In: ACM Symp. on Applied Computing (SAC. pp. 1203{1206 (2010)

    7. Harandi, M.T., Sanderson, C., Wiliem, A., Lovell, B.C.: Kernel analysis over Riemannian manifolds for visual recognition of actions, pedestrians and textures. In: IEEE Works. on Applications of Computer Vision (WACV). pp. 433{439 (2012)

    8. Herath, S., Harandi, M., Porikli, F.: Going deeper into action recognition: A survey. Image and Vision Computing (2017)

    9. Hicheur, H., Kadone, H., Grezes, J., Berthoz, A.: The combined role of motionrelated cues and upper body posture for the expression of emotions during human walking. In: Modeling, Simulation and Optimization of Bipedal Walking. pp. 71{ 85. Springer Berlin Heidelberg (2013)

    10. Jayasumana, S., Hartley, R., Salzmann, M., Li, H., Harandi, M.: Kernel methods on Riemannian manifolds with gaussian rbf kernels. IEEE Trans. on Pattern Analysis and Machine Intelligence 37(12), 2464{2477 (2015)

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