IFCD: Inverted feature extraction for enhancing curling stone detection
The movement data of curling targets is of great significance for the analysis and research of curling. However, in real-life curling competitions, the curling volume is limited and easy to be occluded, and the venue background illumination is complicated. To address these challenges, a curling targ...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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AIP Publishing LLC
2025-01-01
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| Series: | AIP Advances |
| Online Access: | http://dx.doi.org/10.1063/5.0252198 |
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| _version_ | 1832542772680196096 |
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| author | Qian Xiao Zongmin Li Guanlin Li Chaozhi Yang Yun Bai |
| author_facet | Qian Xiao Zongmin Li Guanlin Li Chaozhi Yang Yun Bai |
| author_sort | Qian Xiao |
| collection | DOAJ |
| description | The movement data of curling targets is of great significance for the analysis and research of curling. However, in real-life curling competitions, the curling volume is limited and easy to be occluded, and the venue background illumination is complicated. To address these challenges, a curling target detection model, IFCD, based on Inverted Feature Extraction Network (IFNet) is proposed. IFNet allocates more resources to deal with high-resolution features without introducing additional computational burdens, thus avoiding feature loss caused by inappropriate downsampling. Moreover, a Dynamic Feature Fusion module is introduced in the Neck network to suppress background interference and reduce the feature confusion. In addition, the parameter-independent Four-Scale Decoupled Detection Head is introduced to reduce the conflict between classification and regression tasks and enhance the model’s multi-scale adaptability. IFCD achieves a 0.974 mAP@.5 (Mean Average Precision) on Curling, a regular curling dataset, and 0.723 mAP@.5 on Curling_hard, a complex curling dataset with numerous occlusions. |
| format | Article |
| id | doaj-art-2a66e96dc72544558cd9e3a8699a36b9 |
| institution | Kabale University |
| issn | 2158-3226 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | AIP Publishing LLC |
| record_format | Article |
| series | AIP Advances |
| spelling | doaj-art-2a66e96dc72544558cd9e3a8699a36b92025-02-03T16:40:42ZengAIP Publishing LLCAIP Advances2158-32262025-01-01151015206015206-910.1063/5.0252198IFCD: Inverted feature extraction for enhancing curling stone detectionQian XiaoZongmin LiGuanlin LiChaozhi YangYun BaiThe movement data of curling targets is of great significance for the analysis and research of curling. However, in real-life curling competitions, the curling volume is limited and easy to be occluded, and the venue background illumination is complicated. To address these challenges, a curling target detection model, IFCD, based on Inverted Feature Extraction Network (IFNet) is proposed. IFNet allocates more resources to deal with high-resolution features without introducing additional computational burdens, thus avoiding feature loss caused by inappropriate downsampling. Moreover, a Dynamic Feature Fusion module is introduced in the Neck network to suppress background interference and reduce the feature confusion. In addition, the parameter-independent Four-Scale Decoupled Detection Head is introduced to reduce the conflict between classification and regression tasks and enhance the model’s multi-scale adaptability. IFCD achieves a 0.974 mAP@.5 (Mean Average Precision) on Curling, a regular curling dataset, and 0.723 mAP@.5 on Curling_hard, a complex curling dataset with numerous occlusions.http://dx.doi.org/10.1063/5.0252198 |
| spellingShingle | Qian Xiao Zongmin Li Guanlin Li Chaozhi Yang Yun Bai IFCD: Inverted feature extraction for enhancing curling stone detection AIP Advances |
| title | IFCD: Inverted feature extraction for enhancing curling stone detection |
| title_full | IFCD: Inverted feature extraction for enhancing curling stone detection |
| title_fullStr | IFCD: Inverted feature extraction for enhancing curling stone detection |
| title_full_unstemmed | IFCD: Inverted feature extraction for enhancing curling stone detection |
| title_short | IFCD: Inverted feature extraction for enhancing curling stone detection |
| title_sort | ifcd inverted feature extraction for enhancing curling stone detection |
| url | http://dx.doi.org/10.1063/5.0252198 |
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