| The target detection、tracking and remotely control in the video surveillancehave important significance in the theoretical and practical aspects, but there aremany issues to be addressed in practical applications, especially the problem ofmoving target detection and tracking, how to improve the robustness and the accuracyof the algorithm has been a hot research for scholars. The wireless remote control caras well as the car detection and tracking under video surveillance are both researchedin this paper.First, the overall construction and driving mode of the remote control call areselected according to the tasks, the infrared communication module, motor controlmodule and the main chip module of the car were put emphasis on. Finally, thewireless control between PC and car was achieved. By studying the video movingtarget detection and tracking algorithms commonly used, the advantages of particlefiltering algorithm in the case of non-linear or non-Gaussian are found. Theapplication of particle filter algorithm in video tracking was mainly studied.According to the color characteristics of target in camera surveillance, the colorhistogram of remote control car was chosen as the target modeling, which wasapplied to video surveillance framework of particle filter. The problem of targetdetection and tracking especially when the remote control car was blocked andfast-moving was mainly studied. The results of target detection and tracking based oncolor particle filter algorithm are less than ideal, which showed that the robustness ofthe algorithm is poor. To solve the defects of the algorithm, a new method wasproposed in this paper, in which the color and shape information of the car areadaptively combined based on fuzzy logic to build model. Finally, the improvedmodel was incorporated into the particle filter algorithm. By programming in VS2008and experiments, detection and tracking in new method are better when the target wasblocked or accelerating. |
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