Method for rapidly tracking and positioning set targets in grayscale videos

A gray-scale video, tracking and positioning technology, applied in image data processing, instruments, calculations, etc., can solve the problems of complex tracking process, increased calculation amount and complexity, slowness, etc., and achieve high tracking accuracy, fast calculation speed, Effects of adaptation to scale changes

Inactive Publication Date: 2018-06-29
XIDIAN UNIV
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Problems solved by technology

[0003] However, none of the existing tracking methods can directly adapt to the scene where the target scale changes. The fixed scale makes it not only unable to accurately output the coordinate position of the tracked target in the scene where the target scale changes, but also unable to calibrate the target

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  • Method for rapidly tracking and positioning set targets in grayscale videos
  • Method for rapidly tracking and positioning set targets in grayscale videos
  • Method for rapidly tracking and positioning set targets in grayscale videos

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[0051] In order to further illustrate the technical means and effects of this embodiment to achieve the predetermined purpose, the specific implementation, structural features and effects of this embodiment will be described in detail below in conjunction with the drawings and embodiments.

[0052] The technical solution adopted in this embodiment is mainly divided into four parts: a preprocessing phase, a tracking phase, a parameter learning phase, and a scale prediction phase. In the first frame, it is necessary to artificially specify the position and size of the target in the first frame, and then crop the original image to obtain a standard image centered on the tracking target.

[0053] Step 1: Obtain the current frame tracking window based on the target coordinates and size calculated in the previous frame, and perform logarithmic transformation and cosine window smoothing on the tracking window and the standard target image.

[0054] Step 2: The preprocessed tracking window i...

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Abstract

The invention relates to a method for rapidly tracking and positioning set targets in grayscale videos. The method comprises the following steps of: carrying out two-dimensional Gaussian kernel cyclicconvolution on a standard target image and an image in a video frame sequence to solve cross-correlation matrixes, and processing positions of targets tracked by the cross-correlation matrixes by using ridge regression method; carrying out weighted average on a detection result of the current frame to serve as a next frame of standard target image; self-convoluting each frame of standard target image and solving a statistic feature of each frame of standard target image, and mapping characterization between two frames as scale change so as to solve scale change, in a moving process, of the target; and deconvolution is carried out on an auto-correlation matrix through discrete Fourier transformation and inverse transformation to update and learn a ridge regression parameter which is used for solving a response matrix in the next frame. The method is high in calculation speed and high in tracking precision, adopts dense sampling, is completely adapted to scale change and can be suitablefor the scenes in which targets are moved from far to near or moved from near to far.

Description

technical field [0001] The invention belongs to a single target tracking and positioning technology in video, and in particular relates to a fast tracking and positioning method for a predetermined target in grayscale video. Background technique [0002] Object tracking is a basic research direction of computer vision, which has a wide range of applications in human-computer interaction, monitoring, augmented reality, machine perception and other scenarios. Currently existing tracking methods are mainly divided into two types: generative model algorithms and discriminative model algorithms. The former uses the method of learning target features, and then performs feature matching in the subsequent frame to track the target, while the latter uses the method of learning to build a classifier, and uses the classifier to distinguish the background and the target, so as to achieve the purpose of identifying the target. [0003] However, none of the existing tracking methods can ...

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Application Information

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IPC IPC(8): G06T7/262G06T5/00
CPCG06T7/262G06T5/002G06T2207/10016G06T2207/20056G06T2207/20081
Inventor 闫允一朱江曹起鸣
Owner XIDIAN UNIV
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