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Visual sense tracking method based on target characteristic and bayesian filtering

A technology of Bayesian filtering and visual tracking, which is applied in image data processing, instrumentation, computing, etc., can solve problems such as movement difficulties, achieve high tracking accuracy and improve performance

Inactive Publication Date: 2009-01-07
ZHEJIANG UNIV
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AI Technical Summary

Problems solved by technology

That is to say, the visual tracking problem is regarded as an optimal estimation problem, but the tracking of video targets in real scenes often becomes very difficult due to complex background images and the motion of the target itself
For video targets in complex environments, there are still many difficulties in developing a robust tracking method

Method used

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  • Visual sense tracking method based on target characteristic and bayesian filtering
  • Visual sense tracking method based on target characteristic and bayesian filtering
  • Visual sense tracking method based on target characteristic and bayesian filtering

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Embodiment Construction

[0040] Below in conjunction with example the present invention is described in further detail.

[0041] Taking human body tracking as an example, refer to figure 1 , a visual tracking method based on target features and Bayesian filtering, including the following steps:

[0042] 1) Establish system model and observation model according to the actual movement of the target;

[0043] system modelx k =Ax k-1 +v k

[0044] target state x at time k k =(x,y,v x , v y ,w,h,o w , o h , a x , a y ) T , where (x, y) is the center coordinate of the target; (v x , v y ) is the movement speed of the target center coordinates in the X-axis and Y-axis directions; (w, h) is the width and height of the target area; (o w , o h) is the rate of change of width and height; (a x , a y ) is the acceleration of the target in the direction of X-axis and Y-axis.

[0045] The system state transition matrix A is:

[0046] A = ...

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Abstract

The invention discloses a visual tracking method based on target characteristics and bayes filtration. The method comprises the following steps: a system model and an observation model are established according to the actual motion of a target; the color and the gradient of the target are calculated, similarity function is constructed, and the current observed value of the target is obtained by a particle filter; the state average of particulate matter and the covariance are processed by using karman filtration, thus generating new gauss distribution, then new particulate matter is sampled according the gauss distribution generated, thus calculating weight and output; finally, the particulate matter is sampled again; meanwhile, a partition detection method for the target and the corresponding processing algorithm of shading and non shading are proposed; the visual tracking process is finished. Compared with similar algorithm, the method realizes information complementation between the characteristics by the blending of multi-information, therefore, the target is not easy to be affected by external environmental factors such as light, etc. By adopting the combination of particle filtration and the karman filtration, the tracking accuracy of the whole method is higher, thus improving the tracking performance and being adapted to various complicated environments.

Description

technical field [0001] The invention relates to a video processing and machine vision tracking method based on different characteristics of targets and Bayesian filtering, and is especially suitable for the fields of modern intelligent video monitoring, rapid and accurate search of interested targets, and the like. Background technique [0002] Visual tracking is one of the core topics in the field of computer vision, and it has a wide range of applications in the fields of robot vision, video surveillance, and military target tracking. Intelligent video surveillance system has great application prospects in civilian and military applications. It has been integrated into many residential areas, parking lots, streets, especially in banks, airport security checks and other special occasions that are related to the safety of people's lives and property. The ultimate goal of intelligent video surveillance is to use computer vision and intelligent signal processing and analysis ...

Claims

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Application Information

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IPC IPC(8): G06T7/00G06T7/277
Inventor 徐林忠于慧敏
Owner ZHEJIANG UNIV
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