Semidefinite programming‐based localisation and tracking algorithm using Gaussian mixture modelling

<p class="0abstract"><span lang="EN-US">In order to study the power patrol technology of unmanned aerial vehicle, the tracking algorithm was applied. The automatic patrolling of power lines was discussed in terms of algorithms. An unmanned aerial vehicle transmission line inspection method based on machine vision was proposed. The image and video of the unmanned aerial vehicle inspection of the power line had a complex background. By Wiener filtering de-noising and probability density functions, the image clarity was improved. According to the existing tracking techniques and algorithms, a Camshaft target tracking algorithm based on lossless Kalman filter was proposed. The method of non-destructive Kalman filter was adopted to predict the region of interest of power line identification. Using the Camshaft algorithm, the prediction of the window was searched and the size of the window was adjusted. Transmission lines were tracked in real time. The results showed that the restoration effect of the algorithm was obvious. The clarity of the image was improved. It prepared for the extraction and tracking of the future transmission lines. Therefore, the proposed method provides a feasible way for the UAV power line inspection technology based on machine vision.</span></p>

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“…The two points vote Hought transform inherits the advantages of the stability of Hought. The amount of operation is small [7].…”

Section: The Implementation Of the Improved Phase Marshalling And Hough Transformmentioning

confidence: 99%

Unmanned Aerial Patrol Technology Based on Tracking Algorithm of Target Tracking

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Semidefinite programming‐based localisation and tracking algorithm using Gaussian mixture modelling

Cited by 3 publications

References 25 publications

Unmanned Aerial Patrol Technology Based on Tracking Algorithm of Target Tracking

Unmanned Aerial Patrol Technology Based on Tracking Algorithm of Target Tracking

A Volleyball Movement Trajectory Tracking Method Adapting to Occlusion Scenes

FCN-Attention: A deep learning UWB NLOS/LOS classification algorithm using fully convolution neural network with self-attention mechanism

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