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Matrix Descriptor of Changes (MDC): Activity Recognition Based on Skeleton

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Advanced Concepts for Intelligent Vision Systems (ACIVS 2018)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 11182))

Abstract

A new method called Matrix Descriptor of Changes (MDC) is introduced in this work for description and recognition of human activity from sequences of skeletons. The primary focus was on one of the main problems in this area which is different duration of activities; it is assumed that the beginning and the end are known. Some existing methods use bag of features, hidden Markov models, recurrent neural networks or straighten the time interval by different sampling so that each activity has the same number of frames to solve this problem. The essence of our method is creating one or more matrices with a constant size. The sizes of matrices depend on the vector dimension containing the per-frame low-level features from which the matrix is created. The matrices then characterize the activity, even if we assume that certain activities may have different durations. The principle of this method is tested with two types of input features: (i) 3D position of the skeleton joints and (ii) invariant angular features of the skeleton. All kinds of feature types are processed by MDC separately and, in the subsequent step, all the information gathered together as a feature vector are used for recognition by Support Vector Machine classifier. Experiments have shown that the results are similar to results of the state-of-the-art methods. The primary contribution of proposed method was creating a new simple descriptor for activity recognition with preservation of the state-of-the-art results. This method also has a potential for parallel implementation and execution.

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Acknowledgements

This work was partially supported by Grant of SGS No. SP2018/42, VŠB - Technical University of Ostrava, Czech Republic.

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Authors and Affiliations

  1. Department of Computer Science, FEECS, VŠB - Technical University of Ostrava, 17. listopadu 15, 708 33, Ostrava - Poruba, Czech Republic

    Radek Simkanič

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  1. Radek Simkanič
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Correspondence to Radek Simkanič .

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Editors and Affiliations

  1. DGA, Bagneux, France

    Jacques Blanc-Talon

  2. Laboratoire XLIM, Futuroscope Chasseneuil Cedex, France

    David Helbert

  3. Ghent University, Ghent, Belgium

    Wilfried Philips

  4. CSIRO-ICT Centre, Canberra, ACT, Australia

    Dan Popescu

  5. University of Antwerp, Wilrijk, Belgium

    Paul Scheunders

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Simkanič, R. (2018). Matrix Descriptor of Changes (MDC): Activity Recognition Based on Skeleton. In: Blanc-Talon, J., Helbert, D., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2018. Lecture Notes in Computer Science(), vol 11182. Springer, Cham. https://doi.org/10.1007/978-3-030-01449-0_2

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  • DOI: https://doi.org/10.1007/978-3-030-01449-0_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-01448-3

  • Online ISBN: 978-3-030-01449-0

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