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Human emotion identification from image sequences is highly demanded nowadays. The range of possible applications can varyfrom an automatic smile shutter function of consumer grade digital cameras to Biofied Building technologies, which enablescommunication between building space and residents. The highly perceptual nature of human emotions leads to the complexity oftheir classification and identification. The main question arises from the subjective quality of emotional classification of events thatelicit human emotions. A variety of methods for formal classification of emotions were developed in musical psychology. This workis focused on identification of human emotions evoked by musical pieces using human face tracking and optical flow analysis.Facial feature tracking algorithm used for facial feature speed and position estimation is presented.  Facial features were extractedfrom each image sequence using human face tracking with local binary patterns (LBP) features. Accurate relative speeds of facialfeatures were estimated using optical flow analysis. Obtained relative positions and speeds were used as the output facial emotionvector. The algorithm was tested using original software and recorded image sequences. The proposed technique proves to give arobust identification of human emotions elicited by musical pieces. The estimated models could be used for human emotionidentification from image sequences in such fields as emotion based musical background or mood dependent radio

the international archives of the photogrammetry, remote sensing and spatial information sciences/international archives of the photogrammetry, remote sensing and spatial information sciences

MUSIC-ELICITED EMOTION IDENTIFICATION USING OPTICAL FLOW ANALYSIS OF HUMAN FACE