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- W2365651793 abstract "Target tracking is a hot research project in computer vision and an important problem on many applications,such as detection and tracking of military targets,security guard for communities and important buildings,traffic surveillance in cities and expressways.The goal is to detect and track certain targets according to image sequences.At first,the edge detection of the target of interest is processed after operating the image segmentation based on the background subtraction method.An efficient algorithm of the edge detection according to integrating the edge gradient with the average filter is proposed,which can significantly reduce the sensitivity of the background subtraction method to noise and illumination.Secondly,taking into account the features of the target such as colour,size and etc.,a new modified nearest neighbour(MNN)algorithm for data association using the target features is designed.A Kernel particle filter(KPF)is utilized to estimate the maneuvering target motion.Finally,the algorithm is validated via an example with natural video sequences.The results show the algorithms are effective for target tracking with high accuracy.In complex environment,the algorithms are good too." @default.
- W2365651793 created "2016-06-24" @default.
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- W2365651793 date "2007-01-01" @default.
- W2365651793 modified "2023-09-24" @default.
- W2365651793 title "Visual Target Tracking Based on K-Particle Filter and Edge Detection" @default.
- W2365651793 hasPublicationYear "2007" @default.
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