The accuracy and poor real-time performance of moving objects in a dynamic range complex environment become\nthe bottleneck problem of the target location and tracking. In order to improve the positioning accuracy and the\nquality of tracking service, we propose an embedded tracking algorithm based on multi-feature fusion and visual\nobject compression. On the hand, according to the feature of the target, the optimal feature matching method is\nselected, and the multi-feature crowd fusion location model is proposed. On the other hand, to reduce the dimension\nof the multidimensional space composed of the moving object visual frame and the compression of the visual object,\nthe embedded tracking algorithm is established. Experimental results show that the proposed tracking algorithm has\nhigh precision, low energy consumption, and low delay.
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