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Multiple object tracking(MOT)aims to predict trajectories of all targets and maintain their identities from a given video sequence.In recent years,MOT has gained significant attention and become a hot topic in the field of computer vision due to its huge potential in academic research and practical application.Benefiting from the advancement of object detection and re-identification,the current approaches mainly split the MOT task into three subtasks:object detection,re-identification feature extraction,and data association.This idea has achieved remarkable success.However,maintaining robust tracking still remains challenging due to the factors such as occlusion and similar object interference in the tracking process.To meet the requirement of accurate,robust and real-time tracking in complex scenarios,further research and improvement of MOT algorithms are needed.Some review literature on MOT algorithms has been published.However,the existing literatures do not summarize the tracking approaches comprehensively and lack the latest research achievements.In this paper,the principle of MOT is firstly introduced,as well as the challenges in the tracking process.Then,the latest research achievements are summarized and analyzed.According to the tracking paradigm used to complete the three subtasks,the various algorithms are divided into separate detection and embedding,joint detection and embedding,and joint detection and tracking.The main characteristics of various tracking approaches are described.Afterward,the existing mainstream models are compared and analyzed on MOT challenge datasets.Finally,the future research directions are prospected by discussing the advantages and disadvantages of the current algorithms and their development trends.

In this paper, Ni-SiC nanocoatings were prepared by magnetic field assisted electrodeposition on the surface of cylinder liner. The surface structure and composition of Ni-SiC nanocoatings were studied by using scanning electron microscope (SEM), atomic force microscope ( AFM), transmission electron microscope (TEM) and X-ray diffraction (XRD). When the content of SiC in the plating solution was 6 g/L, the aggregation tendency of SiC nanoparticles was the least, and the surface of the Ni-SiC nanocoating was smooth and compact. In addition, when the content of SiC nanoparticles was 6 g/L, the SiC particle size in the Ni-SiC nanocoating further decreased and distributed uniformly. XRD analysis showed that there were Ni grains and SiC particles in the coatings on the cylinder liner surface. When the content of SiC nanoparticles in the bath was 6 g/ L, the average grain sizes of Ni and SiC particles in Ni-SiC nanocoating were 50.62 and 39.32 nm, respectively. [ABSTRACT FROM AUTHOR]

The effect of quick fuzzy algorithm based on spatial constraint used in yarn evenness test was discussed. A kind of quick fuzzy C mean algorithm based on spatial constraint was put forward. The threshold seg mentation was performed on yarn image. The appearance evenness of ring pure cotton yarns with six different linear densities were tested with the method. The tests show that the algorithm has the advantages of stronger antinoise performance and higher rate of convergence by enlarging the maximum membership degree and restraining the submaximum membership degree at the same time. The test results obtained are close to the test results of USTER CLASAIMATE 5 yarn defect grader. It is considered that it is feasibility for the quick fuzzy algorithm based on spatial constraint used in yarn appearance evenness test. [ABSTRACT FROM AUTHOR]