Moving target tracking method based on KCF and human brain memory mechanism

A moving target and memory technology, applied in the field of computer vision, can solve the problems of lack of adaptive model update strategy, decrease of tracking accuracy of KCF algorithm, inability to deal with complete occlusion of target, etc., achieve fast tracking speed, avoid the process of matrix inversion, Strong anti-occlusion ability

Active Publication Date: 2017-11-21
BEIJING INSTITUTE OF TECHNOLOGYGY
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Problems solved by technology

[0005] On the other hand, although the KCF algorithm has advantages, it also has certain limitations: first, it cannot deal with the problem of complete occlusion of the target; second, it lacks an adaptable model update strategy
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  • Moving target tracking method based on KCF and human brain memory mechanism
  • Moving target tracking method based on KCF and human brain memory mechanism
  • Moving target tracking method based on KCF and human brain memory mechanism

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Embodiment 1

[0053] A target tracking method based on KCF and human brain memory mechanism disclosed in this embodiment, the overall process is as follows figure 1 As shown, it specifically includes the following steps:

[0054] Step 1: Initialize memory space and tracking window.

[0055] Initialize the memory space, first, establish three memory spaces to save the features q of the target matching template respectively t , the parameter α of the classifier t and the classifier target template x t , and each memory space includes short-term memory space and long-term memory space respectively. Then, an instant space is established to save the target data of the current frame, that is, the estimated template.

[0056] Enter the first frame of the video, determine the initial target tracking window, and determine the initial target can be manually selected or determined according to the initial position data of the target.

[0057] Step 2: Calculate the features of the tracking window....

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Abstract

The present invention discloses a moving target tracking method based on the KCF and the human brain memory mechanism. A visual information processing cognitive model based on the human brain memory mechanism is introduced into the target template updating process of the KCF algorithm, and a method based on MTU (Memory-based Template Updating) forms a new model updating strategy, so that each template will be subject to transmission and processing of three spaces of instant memory, short-term memory and long-term memory. In the target tracking process, the target template is updated with different updating strategies according to the matching degree between the target template in the current frame and the target template in the memory space. By effectively remembering the previous scene, the method can keep the robust tracking even when the current target has the sudden change in attitude, reoccurs after temporary disappearance, is sheltered, or the like.

Description

technical field [0001] The invention relates to a method for tracking a moving target in an image sequence, in particular to a method for tracking a moving target based on a kernel correlation filter algorithm (KCF, Kernelized Correlation Filter) and a human brain memory mechanism, and belongs to the technical field of computer vision. Background technique [0002] Moving object tracking is an important research direction in the field of computer vision, which is widely used in intelligent security, visual surveillance, human-computer interaction and other fields. In recent years, although the target tracking technology has made great progress, it is still difficult to achieve accurate target tracking under complex conditions such as illumination changes, target geometric deformation, target occlusion, and fast motion. [0003] At present, the target tracking method based on discrimination has become the mainstream, including: based on structured output tracking with kernel ...

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Application Information

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IPC IPC(8): G06K9/00G06K9/46G06K9/62G06T7/246
CPCG06T7/251G06V20/42G06V10/443G06F18/2453
Inventor 宋勇赵尚男赵宇飞李云李旭
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
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