Engineering slope collapse detection method based on motion detection

Di Wu; Junfeng Zhang; YuLong Shi; Bing Hu

doi:10.1117/12.3024927

14 March 2024 Engineering slope collapse detection method based on motion detection

Di Wu, Junfeng Zhang, YuLong Shi, Bing Hu

Proceedings Volume 13074, Fifth International Conference on Image, Video Processing, and Artificial Intelligence (IVPAI 2023); 1307409 (2024) https://doi.org/10.1117/12.3024927
Event: Fifth International Conference on Image, Video Processing and Artificial Intelligence, 2023, Shenzhen, China

Abstract

In response to the low monitoring efficiency, high personal safety risks, and high labor costs in the inspectionofriverbank slope collapses in river defense engineering, this study proposes an intelligent recognition methodforriverbank slope collapses based on motion detection technology. This method first utilizes a lightweight U-net imagesegmentation model based on attention mechanism for accurate segmentation of the engineering slope region. Then, optical flow is used to identify the motion occurring within the slope region. Finally, a lightweight convolutional neural network is designed to classify the detected moving objects and determine whether they are part of the slope itself.

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

Citation Download Citation

Di Wu, Junfeng Zhang, YuLong Shi, and Bing Hu "Engineering slope collapse detection method based on motion detection", Proc. SPIE 13074, Fifth International Conference on Image, Video Processing, and Artificial Intelligence (IVPAI 2023), 1307409 (14 March 2024); https://doi.org/10.1117/12.3024927

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KEYWORDS

Image segmentation

Engineering

Motion detection

Motion models

Object detection

Optical flow

Detection and tracking algorithms

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