A Robust Parallel Object Tracking Method for Illumination Variations

Illumination variation often occurs in visual tracking, which has a severe impact on the system performance. Many trackers based on Discriminative correlation filter (DCF) have recently obtained promising performance, showing robustness to illumination variation. However, when the target objects undergo significant appearance variation due to intense illumination variation, the features extracted from the object will not have the ability to be discriminated from the background, which causes the tracking algorithm to lose the target in the scene. In this paper, in order to improve the accuracy and robustness of the Discriminative correlation filter (DCF) trackers under intense illumination variation, we propose a very effective strategy by performing multiple region detection and using alternate templates (MRAT). Based on parallel computation, we are able to perform simultaneous detection of multiple regions, equivalently enlarging the search region. Meanwhile the alternate template is saved by a template update mechanism in order to improve the accuracy of the tracker under strong illumination variation. Experimental results on large-scale public benchmark datasets show the effectiveness of the proposed method compared to state-of-the-art methods

Structure Regulation and Application of Bagasse-Based Porous Carbon Material Based on H₂O₂‑Assisted Hydrothermal Treatment

Biomass-based porous carbon has attracted much attention of researchers due to its wide range of raw materials, low cost, and other advantages. It has been also widely used in energy storage devices such as lithium-ion batteries. The carbonization process and final morphology of biomass are indirectly affected by the surface modification and structure optimization of the original biomass. The focus of this study is to prepare porous carbon, which can be used as an electrode material of a lithium-ion battery by surface modification and structure regulation of biomass pretreatment. In this study, the method of H2O2-assisted hydrothermal treatment was used to prepare a kind of bagasse based porous carbon materials that can be used in lithium-ion batteries. The reaction process of H2O2 and bagasse under hydrothermal conditions was explored and described. The results showed that H2O2 promoted the hydrolysis and oxidation of lignocellulose in bagasse and the small molecules obtained from lignocellulose hydrolysis under hydrothermal conditions would be repolymerized to form carbon spheres. The prepared carbon material was applied to the lithium-ion battery. Under a current density of 0.1 A g–1, the specific capacity of 891 mAh g–1 in the first cycle was displayed, and a specific capacity of 453 mAh g–1 was maintained after 150 cycles. At the same time, it showed a good rate performance. After 10 cycles at current densities of 0.1, 0.2, 0.5, 1, 2, and 5 A g–1, the specific capacities of 545, 421, 307, 245, 195, and 133 mAh g–1 were obtained. All the raw materials and products used in this experiment are harmless to the environment, which has certain guiding significance for the structural regulation and green synthesis of lignocellulosic biomass-derived carbon materials