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Location correction long-range tracking algorithm based on continuous correlation filter

A technology of correlation filter and tracking algorithm, applied in the field of visual tracking algorithm, can solve the problems of tracking failure, tracker offset error accumulation, tracking offset, etc., to achieve the effect of continuous target positioning

Active Publication Date: 2017-12-01
HARBIN INST OF TECH AT WEIHAI
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Although target tracking is widely used, long-range tracking in complex scenes is still a challenging issue, because the tracker often causes tracking deviation due to various interference factors, including target occlusion, fast moving and scale changes etc.
Moreover, the offset error of the tracker is easy to accumulate, and it is easy to cause tracking failure in the case of long-distance tracking

Method used

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  • Location correction long-range tracking algorithm based on continuous correlation filter
  • Location correction long-range tracking algorithm based on continuous correlation filter
  • Location correction long-range tracking algorithm based on continuous correlation filter

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Embodiment Construction

[0054] The present invention will be further described below in conjunction with the accompanying drawings.

[0055] The goal of the present invention is to first build a correlation filter in the continuous domain, thereby obtaining higher tracker performance. Suppose the training sample x of the tracker contains D feature channels x 1 ,...,x D , each feature channel x d can generate a corresponding correlation filter weight w d . Then the traditional correlation filter can be obtained by solving the following loss function:

[0056]

[0057] where λ is the regularization parameter (λ≥0), and y is the desired output of the correlation filter, which is the shape of a two-dimensional Gaussian function. ‖f(k)‖ 2 represents the binorm of the sequence f(k), and

[0058] In the proposed algorithm, all parameters involved in the loss function are defined in the continuous domain. But in fact, the feature channel x of the training sample d comes from the extracted image...

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Abstract

The invention relates to the technical field of visual tracking algorithms, in particular to a location correction long-range tracking algorithm based on a continuous correlation filter which has better tracking performance and higher tracking stability. The algorithm includes the following steps: a target is located in a continuous domain; target features are selected by training three templates Rt, Rs and Rd, wherein the target location template Rt encodes the appearance change of the target in real time and needs to be robust to some tracking interference such as fast movement and illumination change, a VGG-19 convolutional neural network is selected and the output features of conv3-4, conv4-4 and conv5-4 layers are used to train the target location template Rt, and in consideration of the computational efficiency, HOG features are used for the Rs and Rd templates; and the target is relocated.

Description

Technical field: [0001] The invention relates to the technical field of visual tracking algorithms, in particular to a continuous correlation filter-based positioning correction long-distance tracking algorithm with better tracking performance and tracking stability. Background technique: [0002] Image or video-based target tracking technology is an important research topic in the field of computer vision, and is widely used in video surveillance, intelligent navigation / assisted driving, intelligent robots, motion behavior analysis and other fields. The basic framework of target tracking is to initialize a rectangular box containing the target of interest in the first frame of the video sequence, and the tracker calibrates the position, area and shape of the target in the next video frame. Although target tracking is widely used, long-range tracking in complex scenes is still a challenging issue, because the tracker often causes tracking deviation due to various interferenc...

Claims

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Application Information

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IPC IPC(8): G06T7/246H04N7/18
CPCG06T2207/20024G06T7/246H04N7/18
Inventor 康文静李欣尤刘功亮
Owner HARBIN INST OF TECH AT WEIHAI
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