Abstract
In order to develop truly intelligent systems, it is necessary to improve their ability to understand non-verbal communication. We propose a novel framework to recognize individuals and emotions from gait, in order to improve HRI. We collected the motion data of the torso from 4 professional actors’ gait, using motion capture system, and 7 non-actors’ using 2 IMU sensors. We developed Feature Value Method which is a PCA based classifier and finally we achieved high recognition rate through cross-validation.
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Zhang, T., Venture, G. (2012). Biometrics from Gait Using Feature Value Method. In: Ramsay, A., Agre, G. (eds) Artificial Intelligence: Methodology, Systems, and Applications. AIMSA 2012. Lecture Notes in Computer Science(), vol 7557. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33185-5_36
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DOI: https://doi.org/10.1007/978-3-642-33185-5_36
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