We propose a novel online multiple object tracker taking structure information into account. State-of-the-art multi-object tracking (MOT) approaches commonly focus on discriminative appearance features, while neglect in different levels structure information and the core of data association. Addressing this, we design a new tracker fully exploiting structure information and encoding such information into the cost function of the graph matching model. Firstly, a new measurement is proposed to compare the structure similarity of two graphs whose nodes are equal. With this measurement, we define a complete matching which performs association in high efficiency. Secondly, for incomplete matching scenarios, a structure keeper net (SKnet) is designed to adaptively establish the graph for matching. Finally, we conduct extensive experiments on benchmarks including MOT2015 and MOT17. The results demonstrate the competitiveness and practicability of our tracker.
This paper extends the quadrature method to price exotic options under jump-diffusion models. We compute the transition density of jump-extended models using convolution integrals. Furthermore, a simpler and more efficient lattice grid is introduced to implement the recursion more directly in matrix form. It can be shown that a lot of running time can be saved. At last, we apply the developed approach to the different jump-extended models to demonstrate its universality and provide a detailed comparison for the discrete path-dependent options to demonstrate its advantages in terms of speed and accuracy.
Two generations of novel linear-dendritic carboxylate surfactants C18-G1-(COONa)2 and C18-G2-(COONa)4 have been synthesized by the divergent method and their structures are characterized by 1H Nuclear Magnetic Resonance and Infrared analysis. The electrical conductivity measurement is used to measure the Krafft temperatures of C18-G1-(COONa)2 and C18-G2-(COONa)4, which are much smaller than those of the corresponding conventional surfactant sodium stearate. The markedly enhanced solubility of two linear-dendritic surfactants is ascribed to the high hydrophilicity of surfactant headgroups induced by the carboxylate and ester groups. The critical micelle concentration (CMC) values obtained from both the electrical conductivity and surface tension measurements indicate that the micellizations of linear-dendritic surfactants become favorable with the increase in the number of the surfactant headgroup. However, the surface activity parameters including the surface tension at the CMC, maximum surface excess, and minimum surface area reveal that C18-G1-(COONa)2 exhibits greater efficiency in absorbing at the air/water interface compared to C18-G2-(COONa)4, owing to their different steric repulsions of the surfactant headgroups. In addition, C18-G1-(COONa)2 and C18-G2-(COONa)4 have higher emulsifying ability than the conventional surfactants sodium stearate and sodium octadecyl sulfate. 相似文献
