UAV Vehicle Tracking Method Based on Embedded Platform

Abstract

The invention discloses a vehicle tracking method for an unmanned aerial vehicle based on an embedded platform, which mainly solves the problem in the prior art that the unmanned aerial vehicle loses tracking when vehicle tracking is blocked. The implementation steps are: 1. Train the vehicle classifier and mark the map; 2. Get a frame of image and initialize the tracking target; 3. Get a frame of image for target tracking; 4. Use the classifier to judge whether the target is blocked, if so, Go to step 5, otherwise go to step 8; 5. Determine whether the target is in the occluded area of ​​the map, if yes, go to step 6, otherwise go to step 7; 6. Perform target detection in the occluded area and make the drone hover, go to step 9; 7. Predict the target position; 8. Control the flight of the UAV according to the target; 9. Determine whether it is over, if so, end the tracking, otherwise return to step 3. The invention can detect and track the blocked target, improves the tracking robustness, and can be used for tracking vehicles on urban roads.

Description

technical field [0001] The invention belongs to the technical field of image processing, and further relates to a vehicle tracking method for an unmanned aerial vehicle, which can be used for vehicle tracking in complex environments on urban roads. Background technique [0002] In recent years, the UAV business has developed rapidly. Due to its simple structure, high flexibility, strong mobility, low cost, and easy to equip various sensors, it can hover and take off and land vertically in complex environments. The machine is an ideal platform to complete tasks such as target detection, target tracking, and monitoring. At present, UAVs have been applied in many target monitoring and tracking fields. [0003] UAV-based vehicle tracking is a typical application. UAV-based vehicle tracking can be used for fugitive hunting, aerial photography based on vehicle tracking, film shooting, etc., which has important practical significance. However, due to complex occlusions such as pe...

AI Technical Summary

Problems solved by technology

The disadvantage of this method is that the entire implementation scheme cannot effectively judge whether the target vehicle is lost. At the same time, although the Kalman filter is used to predict the possible position in the subsequent video after the target is lost, the operator still needs to find the target in the video frame, and automatic tracking cannot be realized.

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