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Facial expressions and subjective assessments of emotions
Affiliation:1. University of Illinois, Springfield, USA;2. Warsaw School of Economics, Poland;3. University of Rzeszów, Poland;1. Departments of Computer Science of Purdue University, USA;2. TU Darmstadt, Germany;3. IMDEA Networks Institute, Spain;4. National Research University Higher School of Economics, St. Petersburg, Russia;5. Steklov Mathematical Institute at St. Petersburg, Russia;6. International Laboratory for Applied Network Research at National Research University Higher School of Economics, Moscow, Russia;1. M.B.E.S. College of Engineering, Ambajogai 431 517, M.S, India;2. Terna Engineering College, Nerul, Navi-Mumbai, M.S, India;1. M.V.Lomonosov Moscow State University, Moscow, Russia;2. Neurocorpus Ltd, Moscow, Russia
Abstract:There was conducted an experimental comparison of the objective (FaceReader 4.0) and subjective assessment of the severity of emotions on different scales. As objects, 18 short (no more than 2 s) videos were used, on which the same person (actress) expressed the given emotions by pronouncing the word “Yes”. These stimuli were selected based on previously conducted subjective scaling experiments. We used (1) a direct subjective quantitative assessment of each video clip separately for each of the parameters selected in the FaceReader 4.0 program (neutral, happy, angry, disgust, fear, sad, surprise) – the severity of the corresponding emotion was evaluated in points; (2) a direct subjective assessment of each video clip for each of the parameters allocated in the 4-dimensional spherical model of emotions (bad – good; confidence – surprise; attraction; defensive reaction: fear – aggression); (3) the methodology of the Semantic Differential Scaling (SD) by C. Osgood; (4) the PXLab Self-Assessment-Manikin Scales. As a result, the relationship of all the scales used was investigated and it was shown that the objective qualification of emotions (using the FaceReader 4.0 program) does not coincide with the results of subjective assessment of the same samples.
Keywords:Emotions  Facial expression recognition  Four-dimensional spherical model of emotions  Semantic differential  FaceReader
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