Neutrosophic similarity measurement-based scale-adaptive visual target tracking method

A scale-adaptive, target tracking technology, applied in the field of computer vision, which can solve problems such as feature influence and uncertainty

Inactive Publication Date: 2018-09-04
SHAOXING UNIVERSITY
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Problems solved by technology

On the one hand, the characteristics of the target itself will be affected by changes in the target pose or external environment; in addition, the tracking frame used to dete

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  • Neutrosophic similarity measurement-based scale-adaptive visual target tracking method

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Embodiment Construction

[0063] In order to describe the technical content of the present invention more clearly, further description will be given below in conjunction with specific embodiments.

[0064] Such as figure 1 The shown scale-adaptive visual target tracking method based on the neutrosophic similarity measure includes the following steps:

[0065] Step 1: Set up a network camera in the monitoring area, and transmit the video data collected by it to the computer terminal in real time.

[0066] Step 2: The computer terminal reads the image data transmitted by the camera in real time in RGB format.

[0067] Step 3: Manually select the target area to be tracked in the initial frame, and calculate the target feature histogram and the initial background histogram. The target feature histogram is calculated by the following formula:

[0068]

[0069] in is the histogram A component of , assuming There are m components, then there is b(x) is a mapping function, which maps the color in...

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Abstract

The invention relates to a neutrosophic similarity measurement-based scale-adaptive visual target tracking method. The method comprises the following steps of: selecting a to-be-tracked target area inan initial frame and calculating a target feature histogram and an initial background histogram; carrying out truth, falsity and indeterminacy measurement aiming at target feature attributes and background feature similarity attributes; establishing a neutrosophic weight vector; introducing the neutrosophic weight vector into a mean shift strategy to determine a target area of a current frame; calculating corresponding truth, falsity and indeterminacy measuring values aiming at scale reducing and expanding and determining a scale updating strategy according to cosine similarity measurement; and updating a target background feature histogram. The method disclosed by the invention has the beneficial effects that an extremely efficient mean shift algorithm is adopted, the corresponding neutrosophic measurement calculating amount is small, the weight vector and scale estimating is low in complexity and high in efficiency and the requirements of real-time target tracking are met; and by utilizing a neutrosophic set theory, the tracking performance of a tracking algorithm coping with challenges of complex backgrounds and like is effectively improved through taking the change of trackedtarget features and the similarity of target / background features into account.

Description

technical field [0001] The invention relates to the technical field of computer vision, in particular to a scale-adaptive visual target tracking method based on neutrosophic similarity measure. Background technique [0002] With the development of science and technology and the improvement of the demand for safe city construction, computer vision applications such as video surveillance, video retrieval, intelligent transportation, and automatic driving are playing an increasingly important role in our lives. However, object tracking, as one of the key technologies, remains a challenging problem. [0003] In the field of object tracking, the mean-shift algorithm is widely used in visual object tracking. During the tracking process, the mean shift algorithm determines the current target position by minimizing the distance between the tracked target and the probability density function of the candidate target area. Since the mean shift tracking algorithm uses color histogram ...

Claims

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Application Information

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IPC IPC(8): G06T7/238G06T7/246G06T5/40G06K9/62
CPCG06T5/40G06T7/238G06T7/246G06T2207/10016G06F18/22
Inventor 胡珂立范恩叶军沈士根樊长兴赵利平
Owner SHAOXING UNIVERSITY
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