Abstract

The main task of object trajectory detection is to collect and synthesize all kinds of information generated in the process of object motion, and get the displacement information of object in 3D space. Vision is one of the important ways for human beings to perceive the external environment and the cognitive world, and it plays a very important role in human life. With the development of computer technology and signal processing technology, a computer vision discipline based on the principle of simulating human eyes has gradually formed. In this paper, an object trajectory detection system based on computer vision is studied to realize object trajectory detection. In this paper, an improved particle filter algorithm is used to track moving objects. The research results show that the improved particle filter algorithm effectively reduces the influence of calculation error and nonlinear error on the measurement system and improves its accuracy. The practical application results show that the measurement error of the system can be controlled at about 5% when considering various error factors, which can meet the needs of practical application.

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