ER-Net: Efficient Recalibration Network for Multi-View Multi-Person 3D Pose Estimation Article Swipe
Mi Zhou
,
Rui Liu
,
Pengfei Yi
,
Dongsheng Zhou
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.32604/cmes.2023.024189
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.32604/cmes.2023.024189
Multi-view multi-person 3D human pose estimation is a hot topic in the field of human pose estimation due to its wide range of application scenarios. With the introduction of end-to-end direct regression methods, the field has entered a new stage of development. However, the regression results of joints that are more heavily influenced by external factors are not accurate enough even for the optimal method. In this paper, we propose an effective feature recalibration module based on the channel attention mechanism and a relative optimal calibration strategy, which is applied to the multi-view multi-person 3D human pose estimation task to achieve improved detection accuracy for joints that are more severely affected by external factors. Specifically, it achieves relative optimal weight adjustment of joint feature information through the recalibration module and strategy, which enables the model to learn the dependencies between joints and the dependencies between people and their corresponding joints. We call this method as the Efficient Recalibration Network (ER-Net). Finally, experiments were conducted on two benchmark datasets for this task, Campus and Shelf, in which the PCP reached 97.3% and 98.3%, respectively.
Related Topics
Concepts
Benchmark (surveying)
Computer science
Pose
Feature (linguistics)
Task (project management)
Range (aeronautics)
Field (mathematics)
Artificial intelligence
Regression
Machine learning
Calibration
Channel (broadcasting)
Joint (building)
Estimation
Pattern recognition (psychology)
Data mining
Statistics
Mathematics
Engineering
Geography
Linguistics
Geodesy
Architectural engineering
Pure mathematics
Aerospace engineering
Philosophy
Computer network
Systems engineering
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.32604/cmes.2023.024189
- https://file.techscience.com/files/CMES/2023/TSP_CMES-136-2/TSP_CMES_24189/TSP_CMES_24189.pdf
- OA Status
- diamond
- Cited By
- 2
- References
- 34
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4319312138
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4319312138Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.32604/cmes.2023.024189Digital Object Identifier
- Title
-
ER-Net: Efficient Recalibration Network for Multi-View Multi-Person 3D Pose EstimationWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-01-01Full publication date if available
- Authors
-
Mi Zhou, Rui Liu, Pengfei Yi, Dongsheng ZhouList of authors in order
- Landing page
-
https://doi.org/10.32604/cmes.2023.024189Publisher landing page
- PDF URL
-
https://file.techscience.com/files/CMES/2023/TSP_CMES-136-2/TSP_CMES_24189/TSP_CMES_24189.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
-
https://file.techscience.com/files/CMES/2023/TSP_CMES-136-2/TSP_CMES_24189/TSP_CMES_24189.pdfDirect OA link when available
- Concepts
-
Benchmark (surveying), Computer science, Pose, Feature (linguistics), Task (project management), Range (aeronautics), Field (mathematics), Artificial intelligence, Regression, Machine learning, Calibration, Channel (broadcasting), Joint (building), Estimation, Pattern recognition (psychology), Data mining, Statistics, Mathematics, Engineering, Geography, Linguistics, Geodesy, Architectural engineering, Pure mathematics, Aerospace engineering, Philosophy, Computer network, Systems engineeringTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
2Total citation count in OpenAlex
- Citations by year (recent)
-
2024: 1, 2023: 1Per-year citation counts (last 5 years)
- References (count)
-
34Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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