| Multi-object tracking is a computer vision task that is commonly used in fields such as intelligent monitoring systems,autonomous driving,and other fields.It aims to continuously detect multiple uncertain numbers of targets from video and provide identity information(ID).It can also stably maintain the original ID of the target when the appearance,location,and scene of the target change,and ultimately obtain a complete and continuous target motion trajectory.In reality,many problems cannot be analyzed and solved without multi target tracking algorithms.However,in practical applications,the number of targets is uncertain,and deformation is prone to occur during movement.Moreover,frequent occlusion and interaction between targets may lead to target ID switching and tracking failure.Therefore,multi target tracking is still a challenging task.This article conducts targeted research on the above issues,and the specific research content is as follows:(1)In order to solve the problem of weak coupling between modules in the traditional detection and tracking paradigm,an integrated multi target tracking algorithm(JDAM)for joint detection,appearance,and motion modeling was proposed.Using a correlation network based on attention mechanism to alleviate the competition between target detection and Re ID tasks,and enhance the collaboration between modules;Propose an attention based scale aware network to address the challenge of target scale changes;Using adaptive graph neural networks to fuse the appearance,motion,and spatiotemporal information of the target to effectively address frequent occlusion issues.(2)Introducing Transformer into multi target tracking,aiming at the advantages and disadvantages of CNN and Transformer in feature extraction,a dual branch parallel backbone network of CNN Transformer is established to fully exploit the advantages of both.The extracted features are fully fused through a two-way bridge model,and parallel decoders are used to output target detection frames and tracking frames respectively,and the two are matched through IOU. |
