Unmanned aerial vehicle aerial video moving target detection method based on time-space-frequency significance

A moving target and detection method technology, applied in the field of computer vision, can solve the problem of low detection accuracy, achieve high execution efficiency, simple algorithm, and improve robustness

Active Publication Date: 2019-05-17
NORTHWESTERN POLYTECHNICAL UNIV
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Problems solved by technology

[0004] In order to avoid the deficiencies of the prior art, the present invention proposes a purpose of the present invention is to apply time-spa

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  • Unmanned aerial vehicle aerial video moving target detection method based on time-space-frequency significance
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  • Unmanned aerial vehicle aerial video moving target detection method based on time-space-frequency significance

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Embodiment Construction

[0057] Now in conjunction with embodiment, accompanying drawing, the present invention will be further described:

[0058] This program adopts the aerial video video moving target detection method based on time-space-frequency saliency, and the specific steps are as follows:

[0059] Step 1: Extract the temporal saliency of the video using the Lucas-Kanade optical flow method.

[0060] Step 2: Use the color distribution to extract the spatial saliency of the image.

[0061] Step 3: Convert the image from the spatial domain to the frequency domain, and use the spectral residual method to extract the frequency domain saliency of the image.

[0062] Step 4: Perform linear weighted fusion of time, space, and frequency domain saliency to obtain a saliency confidence map, binarize the saliency confidence map through an appropriate threshold, and extract moving objects from aerial videos.

[0063] A kind of preferred embodiment step of the present invention is as follows:

[0064]...

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Abstract

The invention relates to an unmanned aerial vehicle aerial video moving target detection method based on time-space-frequency significance. The method comprises the following steps of extracting the time significance of a video by utilizing a Lucas-Kanade optical flow method; extracting the spatial significance of the image by using color distribution; converting an image from a spatial domain toa frequency domain, extracting frequency domain significance of the image by utilizing a spectral residual method, carrying out linear weighted fusion on time, space and frequency domain significanceto obtain a significance confidence map, binarizing the significance confidence map by setting a threshold value, and extracting a moving target from an aerial video, so that the time domain significance, space domain significance and frequency domain significance are fused, the defects of the domains are overcome through the significance of the other two domains, the detection precision and the detection robustness are improved, the algorithm is simple, and the execution efficiency is high.

Description

technical field [0001] The invention relates to a method for detecting a moving target from an aerial video of a drone, belonging to the field of computer vision. Background technique [0002] UAV aerial video moving target detection is one of the important branches in the field of intelligent analysis of aerial video, and it has extremely important applications in military and civilian fields. At present, experts and scholars at home and abroad have done some research work on the detection of moving objects in aerial video. There is an earlier method based on inter-frame difference. First, the adjacent frames are registered based on feature points or regions, and then the registered adjacent frames are differentiated, and the position of the moving target is judged based on the difference image. However, this method is vulnerable to the accuracy of the registration algorithm. If the registration accuracy is not high, the result of the difference is not accurate enough, wh...

Claims

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Application Information

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IPC IPC(8): G06T7/246G06T7/262G06T7/269
Inventor 李映汪亦文李静玉白宗文聂金苗
Owner NORTHWESTERN POLYTECHNICAL UNIV
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