The bird’s nest detection of high voltage tower based on 3D vision technology

Sixing Wang

doi:10.1117/12.3035354

19 July 2024 The bird’s nest detection of high voltage tower based on 3D vision technology

Sixing Wang

Proceedings Volume 13213, International Conference on Image Processing and Artificial Intelligence (ICIPAl 2024); 132132E (2024) https://doi.org/10.1117/12.3035354
Event: International Conference on Image Processing and Artificial Intelligence (ICIPAl2024), 2024, Suzhou, China

Abstract

At present, the main method for detecting foreign objects inside high-voltage towers is manual methods. This method is labor-intensive. To address this issue, this paper proposes a detection method for bird nests in high-voltage towers based on unsupervised depth estimation and 3D reconstruction, which can efficiently and accurately detect bird nests on high-voltage towers and obtain more information. The results showed that after obtaining the depth map information of the bird's nest, the three-dimensional reconstruction method was applied to determine the coordinates of the point cloud. Based on these point cloud information, the 3D model of the bird's nest can be restored, which can minimize subjective judgment errors applied in daily inspections. This method provides a new direction for power system detection.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Sixing Wang "The bird’s nest detection of high voltage tower based on 3D vision technology", Proc. SPIE 13213, International Conference on Image Processing and Artificial Intelligence (ICIPAl 2024), 132132E (19 July 2024); https://doi.org/10.1117/12.3035354

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KEYWORDS

Object detection

Point clouds

Cameras

3D modeling

Feature extraction

3D image processing

Depth maps

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