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Human Action Recognition Algorithm Based on Improved ResNet and Skeletal Keypoints in Single Image
Joint Authors
Fan, Di
Sun, Bo
Chi, Wanda
Lin, Yixue
Sun, Wenxue
Source
Mathematical Problems in Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-06-29
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
Human action recognition is an important part for computers to understand the behavior of people in pictures or videos.
In a single image, there is no context information for recognition, so its accuracy still needs to be greatly improved.
In this paper, a single-image human action recognition method based on improved ResNet and skeletal keypoints is proposed, and the accuracy is improved by several methods.
We improved the backbone network ResNet-50 and CPN to a certain extent and constructed a multitask network to suit the human action recognition task, which not only improves the accuracy but also balances the total number of parameters and solves the problem of large network and slow operation.
In this paper, the improvement methods of ResNet-50, CPN, and whole network are tested, respectively.
The results show that the single-image human action recognition based on improved ResNet and skeletal keypoints can accurately identify human action in the case of different human movements, different background light, and occlusion.
Compared with the original network and the main human action recognition algorithms, the accuracy of our method has its certain advantages.
American Psychological Association (APA)
Lin, Yixue& Chi, Wanda& Sun, Wenxue& Sun, Bo& Fan, Di. 2020. Human Action Recognition Algorithm Based on Improved ResNet and Skeletal Keypoints in Single Image. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1197471
Modern Language Association (MLA)
Lin, Yixue…[et al.]. Human Action Recognition Algorithm Based on Improved ResNet and Skeletal Keypoints in Single Image. Mathematical Problems in Engineering No. 2020 (2020), pp.1-12.
https://search.emarefa.net/detail/BIM-1197471
American Medical Association (AMA)
Lin, Yixue& Chi, Wanda& Sun, Wenxue& Sun, Bo& Fan, Di. Human Action Recognition Algorithm Based on Improved ResNet and Skeletal Keypoints in Single Image. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1197471
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1197471