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RB particle filtering algorithm based on layered space

A particle filter algorithm and layered space technology, applied in computing, image analysis, image data processing and other directions, can solve problems such as difficulty in obtaining and extracting samples

Inactive Publication Date: 2016-06-08
JIANGSU COLLEGE OF INFORMATION TECH
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Problems solved by technology

Doucet has proved that the optimal importance probability density function is q(x k |x k-1 ,z 1∶k )=p(x k |x k-1 ,z k ), but in practical applications, p(x k |x k -1,z k ) is as difficult to obtain as directly sampling from the posterior probability density function

Method used

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  • RB particle filtering algorithm based on layered space
  • RB particle filtering algorithm based on layered space
  • RB particle filtering algorithm based on layered space

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Embodiment Construction

[0028] The present invention will be further explained below.

[0029] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be described in further detail. It should be understood that the specific embodiments described herein are only used to explain the present invention, and not to limit the present invention.

[0030] The algorithm of the present invention is as follows:

[0031] Step one, particle initialization

[0032] Select N particles according to the prior probability p(m(O)) of the target motion model, denoted as m (i) (0). The corresponding weight According to the prior probability of the target state Then the initial state set can be defined as

[0033]

[0034] Step 2: Importance sampling

[0035] Select the optimal distribution p(m(k)|m(k-1), Z 1:k ) As an importance function:

[0036]

[0037] According to the probability, we can get new particles based on importance sampling

[0038]

[0039] S...

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Abstract

The invention discloses an RB particle filtering algorithm based on a layered space and relates to the technical field of particle filtering algorithms. The algorithm disclosed by the invention comprises the following steps: initializing particles, carrying out significance sampling, carrying out particle weight calculation, updating state parameters, and outputting a result. The RB particle filtering algorithm has the beneficial effects that a Rao-Blackwell theorem is applied, and a marginal function is introduced, so that the estimation precision is improved and unbiased estimation is realized; and a layered space method is utilized and is combined with particle filtering, so that the equal precision requirements can be met, the utilization rate of particles is improved, and the quantity of the particles needed by the algorithm is greatly reduced.

Description

Technical field [0001] The present invention relates to the technical field of particle filter algorithms, in particular to an RB particle filter algorithm based on a layered space. Background technique [0002] Intelligent video surveillance is an emerging application direction and a frontier subject that has attracted much attention in the field of computer vision. With the rapid development of network technology and digital video technology, surveillance technology is advancing in the direction of intelligence and networking. Intelligent video surveillance uses computer vision and video analysis methods to automatically analyze the image sequence recorded by the camera without human intervention, so as to realize the positioning, identification and tracking of the target in the dynamic scene, and analyze and judge on this basis Target behavior, which can not only complete daily management but also respond in time when abnormal situations occur. [0003] Particle filtering refe...

Claims

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Application Information

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IPC IPC(8): G06T7/20
CPCG06T2207/10016G06T2207/20016G06T2207/30232
Inventor 季云峰陈芸冯立元匡亮
Owner JIANGSU COLLEGE OF INFORMATION TECH
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