Visual relationship detection method of concrete continuous beam bridge construction scene based on improved ant lion algorithm

Peijun Liu; Qingxin Guo

doi:10.1117/12.3004897

9 October 2023 Visual relationship detection method of concrete continuous beam bridge construction scene based on improved ant lion algorithm

Peijun Liu, Qingxin Guo

Author Affiliations +

Proceedings Volume 12791, Third International Conference on Advanced Algorithms and Neural Networks (AANN 2023); 1279111 (2023) https://doi.org/10.1117/12.3004897
Event: Third International Conference on Advanced Algorithms and Neural Networks (AANN 2023), 2023, Qingdao, SD, China

Abstract

Due to the lack of sufficient training samples, it is not possible to accurately identify the visual relationships of concrete continuous beam bridge construction scenes, resulting in a low detection recall rate. Therefore, a new visual relationship detection method for building scenes is proposed. Perform feature fusion and optimization processing on the construction scene, extract unique features and spatial distribution features of the construction scene, use an improved ant lion algorithm to simulate the walking motion of ants searching for food, establish a matrix, obtain local optimal solutions, and then detect the visual relationship of the construction scene. Experimental analysis shows that after the application of the new method, the recall rate of visual relationship detection has significantly improved, reaching over 96%.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Peijun Liu and Qingxin Guo "Visual relationship detection method of concrete continuous beam bridge construction scene based on improved ant lion algorithm", Proc. SPIE 12791, Third International Conference on Advanced Algorithms and Neural Networks (AANN 2023), 1279111 (9 October 2023); https://doi.org/10.1117/12.3004897

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KEYWORDS

Visualization

Bridges

Object detection

Detection and tracking algorithms

Image enhancement

Image processing

Feature fusion

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