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Probability prediction type target tracking method

A probabilistic prediction and target tracking technology, applied in the field of target tracking, can solve problems such as inaccurate data and difficulty in accurately determining the target model

Active Publication Date: 2015-10-28
阳光暖果(北京)科技发展有限公司
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AI Technical Summary

Problems solved by technology

[0003] Disadvantages of the traditional target tracking algorithm: When the characteristics of the target are well understood, the corresponding model can be easily found by using the multi-model method, so that the accuracy of target tracking is more accurate
However, when the target characteristics are not known, this method can only use common models and use a series of different parameters to model, so it is difficult to accurately determine the target model; Competition is also more intense, making tracking data imprecise

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Embodiment Construction

[0058] In order to further explain the technical means and effects adopted by the present invention to achieve the intended invention purpose, the specific implementation, features and effects of the probabilistic prediction-type target tracking algorithm proposed according to the present invention are as follows: the camera collects data And identify the target, give the coordinates of the target, as the input of this algorithm.

[0059] Such as figure 1 As shown, the specific operation steps of the probabilistic prediction type target tracking method proposed by the present invention are as follows:

[0060] Step 1: Start kalman filter

[0061] Enter the observed data into the system. Extract the first 2 observations.

[0062] According to these two values, the two coordinates are calculated accordingly, and the initial position and initial coordinates can be obtained, namely value; The value of takes the identity matrix.

[0063] Step 2: kalman filtering

[0064] Acc...

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Abstract

The present invention relates to a probability prediction type target tracking method and is mainly applied to an intelligent machine. However, according to an existing target tracking algorithm, only a track after target filtering is given, so that the target tracking has a delay, and because a complete model in a complex environment can not be obtained, the conventional target tracking algorithm has a limitation in practical application. In order to change the existing state and enable the target tracking method to be suitable for a changeable and complex environment, a new thought framework is proposed, wherein the intelligent machine can detect whether a target object is performing a non-motorized motion, and once the target enters a non-motorized motion stage, the intelligent machine starts Kalman filtration and is capable of giving out results of prediction and tracking in the form of probability.

Description

technical field [0001] The invention relates to a target tracking method, in particular to a probabilistic prediction type target tracking method, which is applied in the field of target tracking. Background technique [0002] The existing target tracking algorithm only gives the track of the target after filtering, which has a certain delay, and because the complete model in the complex environment cannot be obtained, the traditional target tracking algorithm has certain limitations in the complex environment. Such as interactive multi-model and variable-structure interactive multi-model: the purpose of this method is to build a relatively complete target model, and then perform a series of tracking predictions on the target. [0003] Disadvantages of the traditional target tracking algorithm: When the characteristics of the target are well known, the corresponding model can be easily found by using the multi-model method, so that the accuracy of target tracking is more acc...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F19/00
Inventor 康一梅夏洋
Owner 阳光暖果(北京)科技发展有限公司
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