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- W2373843639 abstract "Against the defect of the optimal estimation achieved by models or functions approximation in the nonlinear target tracking,this paper proposes a sequential Monte Carlo filter tracking algorithm based on inter-frame prediction and feature matching.In the algorithm,the state of vehicle tracked is described by the weighted spatiograms in HSV color space,the samples relay is completed by a normal random drift model,the computation of the sample weights is also achieved by the similarity measure between sample and target,and the posterior probability of state vector is computed by the weighted samples.The experiment research shows that this approach is simple and computationally efficient and can track the irregular and nonlinear moving vehicles real time and accurately in a complex environment.In addition,the means can also deal with the situations of partial occlusion and short-term loss as well." @default.
- W2373843639 created "2016-06-24" @default.
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- W2373843639 date "2012-01-01" @default.
- W2373843639 modified "2023-09-24" @default.
- W2373843639 title "Vehicle Tracking Algorithm based on Sequential Monte Carlo Filter" @default.
- W2373843639 hasPublicationYear "2012" @default.
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