Video-Based Rope Skipping Repetition Counting with ResNet Model

Xinxin Li; Jiawen  Wang

doi:10.18535/ijecs/v10i11.4631

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Xinxin Li, Jiawen Wang,

Article Date Published : 12 November 2021 | Page No.: 25413-25419 |

DOI https://doi.org/10.18535/ijecs/v10i11.4631

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Abstract

Video Repetition Counting is one of the important research areas in computer vision. It focuses on estimating the number of repeating actions. In this paper, we propose a method for video-based rope skipping repetition counting that combines the ResNet Model and a counting algorithm. Each frame in the given video is first classified into two categories: upward and downward, describing its current motion status. Then the classification sequence of the video is processed by a statistical counting algorithm to obtain the final repetition number. The experiments on real-world videos show the efficiency of our model.

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Xinxin Li

Shandong University of Technology
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Jiawen Wang

Cangzhou Technical College, China

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Cangzhou Technical College, China

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International Journal of Engineering and Computer Science, 2021.

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Article Details

Issue: Vol. 10 No. 11 (2021)

Page No.: 25413-25419

Section: Articles

DOI: https://doi.org/10.18535/ijecs/v10i11.4631

How to Cite

Li, X., & Wang, J. . (2021). Video-Based Rope Skipping Repetition Counting with ResNet Model. International Journal of Engineering and Computer Science, 10(11), 25413–25419. https://doi.org/10.18535/ijecs/v10i11.4631

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Video-Based Rope Skipping Repetition Counting with ResNet Model

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