仿生模式识别目标自适应跟踪算法

doi:10.3969/j.issn.1001-2400.2013.04.024

Abstract

Abstract:

A new method for image object recognition and tracking based on Biomimetic Pattern Recognition (BPR), which can automatically change the size of the object, is proposed. To accomplish the learning process of the sample objects with different sizes, an artificial neural network model is used to cover the training sample. The curve fitting method based on the Radial Basis Function (RBF) neural network is presented to approximate the size of the objects in the coverage of the network formed by BPR theory in order to change the size of the object automatically. The Quadratic Minimum Distance algorithm based on the Euclidean distance is applied to search the target in the process of object recognition and tracking. Experimental results and theoretical analysis show that the algorithm proposed in this paper is more effective and robust in object recognition and tracking of video image sequences than the BP neural network.

Key words: biomimetic pattern recognition, target tracking, curve fitting, quadratic minimum distance, neural network

CLC Number:

TN911.73

LIU Huanyun;WANG Junning;HE Di;TU Shangbin. Research on biomimetic pattern recognition for object adaptive tracking algorithm[J].J4, 2013, 40(4): 142-148.

References

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Research on biomimetic pattern recognition for object adaptive tracking algorithm

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