Development and algorithm analysis of unmanned aerial vehicle software based on tracking and detecting multiple targets
There are still many problems in the current multi target tracking and detection of unmanned aerial vehicles,such as low accuracy and large memory usage.Based on this,the YOLOv5 algorithm and DeepSort algorithm are used to complete the development of unmanned aerial vehicle software,and a tracking template update strategy is designed.Through the detection module,relevant information such as target confidence and confidence are transmitted to the tracking module to implement tracking.Under the application of YOLOv5 algorithm and DeepSort algorithm,the prediction of target estimation can be achieved,and the prediction results can be allocated to ensure the tracking effect and speed of unmanned aerial vehicles.The final experimental results found that the drone software based on YOLOv5 algorithm and DeepSort algorithm can improve tracking accuracy by 22%in multi target tracking,with significant results.
tracking and detectionmultiple objectivesdrone software developmentalgorithm
万方数据
维普
