Open AccessVideo-Based Rope Skipping Repetition Counting with ResNet Model
Author(s) -
Xinxin Li,
Jiawen Wang
Publication year - 2021
Publication title -
international journal of engineering and computer science
Language(s) - English
Resource type - Journals
ISSN - 2319-7242
DOI - 10.18535/ijecs/v10i11.4631
Subject(s) - computer science , repetition (rhetorical device) , rope , frame (networking) , computer vision , artificial intelligence , sequence (biology) , algorithm , telecommunications , philosophy , linguistics , biology , genetics
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.