Local Temporal Block Difference Pattern for Action Recognition in Surveillance Videos using Tree Based Classifiers

  • Authors

    • Poonkodi M SRM Institute of Science and Technology
    • Vadivu G SRM Institute of Science and Technology
    2018-07-10
    https://doi.org/10.14419/ijet.v7i3.11645
  • Action Recognition, Decision Tree, Random Forest, REPTree, Temporal Difference.

  • Abstract

    Intelligent video classification and prediction is a fundamental step towards effective retrieval system. Huge volume of video is available for navigation today and managing such video and prediction of the activity before its completion gains importance in video surveillance,human computer recognition, gesture recognition etc., An eminent Local Temporal Block Difference Pattern (LTBDP) is introduced

    which enable efficient feature extraction that could be given to Tree Classifiers like Random Forest and REPTree for further prediction.The proposed pattern has been evaluated on UT-interaction dataset which enable researchers to predict ongoing human actions in an efficient manner. Experimental results using LTBDP in Random Forest and REPTree classifier gives 85.6% and 66.45% accuracy respectively.

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  • How to Cite

    M, P., & G, V. (2018). Local Temporal Block Difference Pattern for Action Recognition in Surveillance Videos using Tree Based Classifiers. International Journal of Engineering & Technology, 7(3), 1405-1409. https://doi.org/10.14419/ijet.v7i3.11645

    Received date: 2018-04-16

    Accepted date: 2018-05-30

    Published date: 2018-07-10