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Application Development for Hand Gestures Recognition with Using a Depth Camera

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Databases and Information Systems (DB&IS 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1243))

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Abstract

The aim of the work is to develop an application for hand gestures identification based on a convolutional neural network using the TensorFlow & Keras deep learning frameworks. The gesture recognition system consists of a gesture presentation, a gesture capture device (sensor), the preprocessing and image segmentation algorithms, the features extraction algorithm, and gestures classification. As a sensor, Intel® Real Sense™ depth camera D435 with USB 3.0 support for connecting to a computer was used. For video processing and extraction both RGB images and depth information from the input data, functions from the Intel Real Sense library are applied. For pre-processing and image segmentation algorithms computer vision methods from the OpenCV library are implemented. The subsystem for the features extracting and gestures classification is based on the modified VGG-16, with weights previously trained on the ImageNet database. Performance of the gesture recognition system is evaluated using a custom dataset. Experimental results show that the proposed model, trained on a database of 2000 images, provides high recognition accuracy (99.4%).

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Acknowledgements

This work has been supported by the Ministry of Digital Development, Innovations and Aerospace Industry of the Kazakhstan Republic under project № AP06850817.

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Authors and Affiliations

  1. National Research Nuclear University “MEPhI”, 31 Kashirskoe Road, 115409, Moscow, Russian Federation

    Dina Satybaldina

  2. L.N. Gumilyov Eurasian National University, 11 Pushkin Street, 010008, Nur-Sultan, Kazakhstan

    Dina Satybaldina, Gulziya Kalymova & Natalya Glazyrina

Authors
  1. Dina Satybaldina
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  2. Gulziya Kalymova
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  3. Natalya Glazyrina
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Corresponding author

Correspondence to Dina Satybaldina .

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Editors and Affiliations

  1. Department of Computer Systems, Tallinn University of Technology, Tallinn, Estonia

    Tarmo Robal

  2. Department of Software Science, Tallinn University of Technology, Tallinn, Estonia

    Hele-Mai Haav

  3. Department of Software Science, Tallinn University of Technology, Tallinn, Estonia

    Jaan Penjam

  4. Institute of Computer Science, University of Tartu, Tartu, Estonia

    Raimundas Matulevičius

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Satybaldina, D., Kalymova, G., Glazyrina, N. (2020). Application Development for Hand Gestures Recognition with Using a Depth Camera. In: Robal, T., Haav, HM., Penjam, J., Matulevičius, R. (eds) Databases and Information Systems. DB&IS 2020. Communications in Computer and Information Science, vol 1243. Springer, Cham. https://doi.org/10.1007/978-3-030-57672-1_5

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  • DOI: https://doi.org/10.1007/978-3-030-57672-1_5

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