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Dynamic Gesture Recognition Based on Edge Feature Enhancement Using Sobel Operator

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Book cover E-Learning and Games (Edutainment 2017)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10345))

Abstract

Aimed at the present situation that dynamic hand gestures recognition rate is low and the effect is not ideal, this paper uses Sobel operator to detect the edges in gesture image sequences, enhancing the edge features in dynamic gesture image. In order to prevent the information loss of gesture image after edge detection, the paper will fuse the HOG, HOG2 feature of gesture image sequences after edge detection with that of the original gesture image sequences to enhance edge features without losing other information. In the experiments, Nearest Neighbor Interpolation (NNI) is used to normalize the image sequences to the same length with all gesture video from CVRR-HANDS 3D database, then Sobel operator is used to detect the edges in all gesture image sequences (including RGB data and the Depth data) for subsequent processing, we called edge detection image sequences for Sobel CVRR-HANDS 3D database, the original data for NonSobel CVRR-HANDS 3D database. Next we extract the HOG and HOG2 features from NonSobel CVRR-HANDS 3D database and Sobel CVRR-HANDS 3D database, and incorporating these features. Finally, we respectively use Support Vector Machine (SVM) of the linear Kernel (LIN) and Histogram intersection Kernel (HIK) to recognize dynamic hand gestures. The experimental results show that the recognition rate from our method improves more than two percentage points compared with the traditional method on LIN and HIK kernel of SVM.

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Author information

Authors and Affiliations

  1. Zhejiang University, Hangzhou, China

    Mingmin Zhang & Shengle Zhou

  2. Jiangnan University, Wuxi, China

    Bing Wang

  3. Hangzhou Normal University, Hangzhou, China

    Zhigeng Pan

Authors
  1. Mingmin Zhang
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  2. Bing Wang
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  3. Shengle Zhou
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  4. Zhigeng Pan
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Corresponding author

Correspondence to Zhigeng Pan .

Editor information

Editors and Affiliations

  1. Bournemouth University, Bournemouth, United Kingdom

    Feng Tian

  2. Bournemouth University, Bournemouth, United Kingdom

    Christos Gatzidis

  3. Liverpool John Moores University, Liverpool, United Kingdom

    Abdennour El Rhalibi

  4. Bournemouth University, Bournemouth, United Kingdom

    Wen Tang

  5. Bournemouth University, Bournemouth, United Kingdom

    Fred Charles

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Zhang, M., Wang, B., Zhou, S., Pan, Z. (2017). Dynamic Gesture Recognition Based on Edge Feature Enhancement Using Sobel Operator. In: Tian, F., Gatzidis, C., El Rhalibi, A., Tang, W., Charles, F. (eds) E-Learning and Games. Edutainment 2017. Lecture Notes in Computer Science(), vol 10345. Springer, Cham. https://doi.org/10.1007/978-3-319-65849-0_16

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  • DOI: https://doi.org/10.1007/978-3-319-65849-0_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-65848-3

  • Online ISBN: 978-3-319-65849-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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