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Robust long-range target tracking method based on correlation filtering and deep Siamese network

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: 2020-04-14
XIAMEN UNIV
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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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  • Robust long-range target tracking method based on correlation filtering and deep Siamese network
  • Robust long-range target tracking method based on correlation filtering and deep Siamese network
  • Robust long-range target tracking method based on correlation filtering and deep Siamese network

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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

Robust long-range target tracking method based on correlation filtering and deep Siamese network, involving computer vision technology. By combining correlation filtering and deep twin network under a unified tracking framework, it can effectively deal with challenges such as target occlusion and disappearing field of view in long videos. In this tracking method, the proposed expert evaluation mechanism based on D-expert and C-expert can effectively evaluate and screen the target candidate positions jointly generated by correlation filtering and deep twin network, and obtain the best target tracking results. This result is used to update the correlation filter tracker, which effectively avoids the correlation filter tracker being updated by wrong samples. The proposed object tracking method is robust to various challenges in long videos, and can track objects stably 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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Patent Type & Authority Patents(China)
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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