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Correlation filtering and deep twin network-based robust long-range target tracking method

A technology of correlation filtering and twin network, applied in the field of robust long-range target tracking, can solve the problems of unsatisfactory tracking effect and lack of updates

Active Publication Date: 2018-11-02
XIAMEN UNIV
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AI Technical Summary

Problems solved by technology

This method can achieve much faster than real-time tracking speed, but due to the lack of online updates, when the target appearance changes drastically, the tracking effect is not ideal

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  • Correlation filtering and deep twin network-based robust long-range target tracking method
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  • Correlation filtering and deep twin network-based robust long-range target tracking method

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Embodiment Construction

[0048] The method of the present invention will be described in detail below in conjunction with the accompanying drawings and embodiments.

[0049] see figure 1 , the implementation of the embodiment of the present invention includes the following steps:

[0050] 1) Given a frame of training video, delineate the training area centered on the target, which completely includes the target and part of the background area. The division method is as follows: with the target as the center, a rectangular training area is constructed, and the length and width of the rectangular area are respectively the length and width of the target; if the rectangular area exceeds the training video frame, the average pixel is used to fill it.

[0051] 2) Use the pre-trained VGG-Net-19 model to extract CNN features from the training area obtained in step 1). The specific process is as follows: Use bilinear interpolation on the rectangular training area obtained in step 1), change its size to make ...

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Abstract

The invention discloses a correlation filtering and deep twin network-based robust long-range target tracking method, and relates to a computer vision technology. According to the method, correlationfiltering and a deep twin network are combined under a uniform tracking framework, so that challenges of target occlusion and view disappear in long videos can be effectively processed. In the tracking method, a D-expert and C-expert-based expert assessment mechanism is capable of effectively assessing and screening target candidate positions jointly generated by the correlation filtering and thedeep twin network so as to obtain optimum target tracking results, and the results are used for updating correlation filtering trackers, so that the condition that the correlation filtering trackers are updated by wrong samples is effectively avoided. The target tracking method is relatively robust for various challenges in long videos, and is capable of stably tracking targets for a long time.

Description

technical field [0001] The invention relates to computer vision technology, in particular to a robust long-range target tracking method based on correlation filtering and a deep twin network. Background technique [0002] As a basic research topic in the field of computer vision, object tracking has a wide range of applications in video surveillance, human-computer interaction, virtual reality, intelligent robots, and autonomous driving. After a long period of research, a large number of excellent target tracking algorithms have emerged in the field of target tracking. According to the length of the video to be processed, the target tracking algorithm can be divided into short-range target tracking algorithm and long-range target tracking algorithm. In practical applications, short-range target tracking algorithms cannot accurately track targets for a long time because targets often experience challenges such as long-term occlusion, rotation, and lighting. Therefore, it is...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/62G06N3/04
CPCG06V20/40G06V20/46G06N3/045G06F18/214
Inventor 王菡子吴强强严严
Owner XIAMEN UNIV
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