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Probabilistic Neural Network Based Dance Gesture Recognition

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Gesture Recognition

Part of the book series: Studies in Computational Intelligence ((SCI,volume 724))

Abstract

With the growing interest in the domain of human computer interaction these days, budding research professionals are coming up with novel ideas of developing more versatile and flexible modes of communication between a man and a machine. Using the attributes of internet, the scientists have been able to create a web based social platform for learning any desired art by the subject himself/herself, and this particular procedure is termed as electronic learning or e-learning . In this chapter, we propose a novel application of gesture dependent e-learning of dance . This e-learning procedure may provide help to many dance enthusiasts who cannot learn the art because of scarcity of resources despite having great zeal. The chapter mainly deals with recognition of different dance gestures of a trained user such that after detecting the discrepancies between the gestures shown and actually performed by a novice; the user can rectify his faults. The elementary knowledge of geometry has been employed to introduce the concept of planes in the feature extraction stage. Actually, five planes have been constructed to signify major body parts while keeping the synchronous parts in one unit. Then four distances and four angular features have been obtained to provide entire positional information of the different body joints. Finally, using a probabilistic neural network the dance gestures have been classified after training the said network with sufficient amount of data recorded from numerous subjects to maintain generality. To check the capability of the discussed method, it has been compared with various standard classifiers in terms of performance indices and in each case the proposed framework has surpassed or provided nearly equal performance as given by the other networks.

Contributed by Sriparna Saha, Rimita Lahiri and Amit Konar

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Authors and Affiliations

  1. Artificial Intelligence Laboratory, Department of Electronics and Tele-Communication Engineering, Jadavpur University, Kolkata, India

    Amit Konar

  2. Artificial Intelligence Laboratory, Department of Electronics and Tele-Communication Engineering, Jadavpur University, Kolkata, India

    Sriparna Saha

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  1. Amit Konar
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  2. Sriparna Saha
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Correspondence to Amit Konar .

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Konar, A., Saha, S. (2018). Probabilistic Neural Network Based Dance Gesture Recognition. In: Gesture Recognition. Studies in Computational Intelligence, vol 724. Springer, Cham. https://doi.org/10.1007/978-3-319-62212-5_6

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  • DOI: https://doi.org/10.1007/978-3-319-62212-5_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-62210-1

  • Online ISBN: 978-3-319-62212-5

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