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Enhanced Estimation Algorithm Based on YOLOv8n-Pose Key Point Features
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Xiantao YIN1, Bo HU1, *, Sizhao LI2
Radio Communications Technology | 2025, 51(5) : 1025 - 1035
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Radio Communications Technology | 2025, 51(5): 1025-1035
• Special Topic:Frontiers in Intelligent Communication, Storage, and Information Processing Technologies •
Enhanced Estimation Algorithm Based on YOLOv8n-Pose Key Point Features
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Xiantao YIN1, Bo HU1, *, Sizhao LI2
Affiliations
  • 1.School of Big Data and Computer Science, Guizhou Normal University, Guiyang 550025, China
  • 2.College of Computer Science and Technology, Harbin Engineering University, Harbin 150001, China
Published: 2025-09-18 doi: 10.3969/j.issn.1003-3114.2025.05.015
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Existing key point detection algorithms tend to suffer from reduced detection precision, missed detections, or misaligned key points in scenarios with varying lighting conditions and dense crowds with overlapping figures. To address this issue, an improved LBW-YOLOv8n-Pose algorithm for multi-person pose estimation in complex environments is proposed based on YOLOv8n-Pose. By introducing the Large Separable Kernel Attention (LSKA) in the Spatial Pyramid Pooling-Fast (SPPF) layer of the feature extraction backbone network, the algorithm enhances the image feature representation and perception capabilities. A weighted Bidirectional Feature Pyramid Network (BiFPN) is incorporated in the neck network for reconstruction to improve the multi-scale feature fusion effect. Additionally, an improved Wise-IoU loss function is adopted to accelerate the model's convergence speed and enhance its robustness in complex scenarios. Experimental results show that the improved model achieves precision, recall, and average detection precision of 85.7%, 76.8%, and 81.7% respectively on the MS-COCO2017 human key point dataset, representing significant improvements over the original model. Moreover, it can more accurately and effectively detect key point information of multiple people in complex situations.

pose estimation  /  attention mechanism  /  YOLOv8n-Pose
Xiantao YIN, Bo HU, Sizhao LI. Enhanced Estimation Algorithm Based on YOLOv8n-Pose Key Point Features[J]. Radio Communications Technology, 2025 , 51 (5) : 1025 -1035 . DOI: 10.3969/j.issn.1003-3114.2025.05.015
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Article Info
doi: 10.3969/j.issn.1003-3114.2025.05.015
  • Receive Date：2025-05-13
  • Online Date：2026-04-17
  • Published：2025-09-18
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  • Received：2025-05-13
Affiliations
    1.School of Big Data and Computer Science, Guizhou Normal University, Guiyang 550025, China
    2.College of Computer Science and Technology, Harbin Engineering University, Harbin 150001, China
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