Laser & Optoelectronics Progress, Volume. 58, Issue 4, 0410011(2021)
Photogrammetric Coded Point Localization Based on Target Detection Network
Fig. 1. Coded markers. (a) Structure of coding; (b) scale of cross coding
Fig. 2. Detection flow of YOLO v3
Fig. 3. Bottleneck layer
Fig. 4. Transition layer
Fig. 5. Dense residual block
Fig. 6. Backbone network of improved YOLO v3
Fig. 7. False mark points
Fig. 8. Center positioning of coded points. (a) Target segmentation; (b) pretreatment; (c) centroid extraction; (d) center positioning
Fig. 9. Precision-Recall curves of model
Fig. 10. Comparison of detection effect of two experiments for the same photo. (a) Experiment 1; (b) experiment 1
Fig. 11. Test results in different environments
Fig. 12. Nearest distance comparison
Fig. 13. Influence of salt-and-pepper noise on recognition rate
Fig. 14. Influence of Gaussian noise on recognition rate
Fig. 15. Decoding results. (a) Poor condition; (b) good condition
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Dahui Qin, Dong Cheng, Mingzhu Su, Yunfei Duan, Yongbo Shao. Photogrammetric Coded Point Localization Based on Target Detection Network[J]. Laser & Optoelectronics Progress, 2021, 58(4): 0410011
Category: Image Processing
Received: Jun. 28, 2020
Accepted: Aug. 7, 2020
Published Online: Feb. 8, 2021
The Author Email: Cheng Dong (chengdong203@qq.com)