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Human Action Recognition Algorithm Based on Improved ResNet and Skeletal Keypoints in Single Image
المؤلفون المشاركون
Fan, Di
Sun, Bo
Chi, Wanda
Lin, Yixue
Sun, Wenxue
المصدر
Mathematical Problems in Engineering
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-12، 12ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-06-29
دولة النشر
مصر
عدد الصفحات
12
التخصصات الرئيسية
الملخص 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.
نمط استشهاد جمعية علماء النفس الأمريكية (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
نمط استشهاد الجمعية الأمريكية للغات الحديثة (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
نمط استشهاد الجمعية الطبية الأمريكية (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
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1197471
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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