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Canine Behavior Interpretation Framework Using Deep Graph Model

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Artificial Intelligence and Soft Computing (ICAISC 2021)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12854))

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Abstract

Humans have long aspired to understand dog behavior. While research on the Calming signal has achieved substantial progress in understanding dog behavior, it remains an unfamiliar concept to non-expertise. Therefore, in this paper, we introduce a framework for analyzing dog behavior, which defines the interrelationship between dog postures through a graph model without any additional devices but a camera. First of all, our framework classifies the dog posture in frame units, using a machine learning model based on the position information of the dog’s body part in the video captured by the camera. We then analyze dog behavior using graph models that define interrelationships among classified dog postures. We expect that our approach will help non-expertise to understand dog behavior.

This research was partly supported by the MSIT(Ministry of Science and ICT), Korea, under the Grand Information Technology Research Center support program(IITP-2021-2015-0-00742) and Institute of Information & communications Technology Planning & Evaluation (IITP) (No. 2020-0-00990, Platform Development and Proof of High Trust & Low Latency Processing for Heterogeneous\(\cdot \)Atypical\(\cdot \)Large Scaled Data in 5G-IoT Environment).

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Author information

Authors and Affiliations

  1. Sungkyunkwan University, Suwon, Korea

    Jongmin Lim, Donghee Kim & Kwangsu Kim

Authors
  1. Jongmin Lim
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  2. Donghee Kim
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  3. Kwangsu Kim
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Corresponding author

Correspondence to Jongmin Lim .

Editor information

Editors and Affiliations

  1. Czestochowa University of Technology, Częstochowa, Poland

    Leszek Rutkowski

  2. Częstochowa University of Technology, Częstochowa, Poland

    Rafał Scherer

  3. Częstochowa University of Technology, Częstochowa, Poland

    Marcin Korytkowski

  4. Edmonton, AB, Canada

    Witold Pedrycz

  5. AGH University of Science and Technology, Krakow, Poland

    Ryszard Tadeusiewicz

  6. Electrical and Computer Engineering, University of Louisville, Louisville, KY, USA

    Jacek M. Zurada

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Lim, J., Kim, D., Kim, K. (2021). Canine Behavior Interpretation Framework Using Deep Graph Model. In: Rutkowski, L., Scherer, R., Korytkowski, M., Pedrycz, W., Tadeusiewicz, R., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2021. Lecture Notes in Computer Science(), vol 12854. Springer, Cham. https://doi.org/10.1007/978-3-030-87986-0_9

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  • DOI: https://doi.org/10.1007/978-3-030-87986-0_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-87985-3

  • Online ISBN: 978-3-030-87986-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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