Self-adaptive coal mining machine follow-up tracking multi-camera video splicing method

A follow-up tracking, multi-camera technology, applied in image enhancement, image analysis, image data processing, etc., can solve the problem that dynamic large-scale target follow-up monitoring has not been fully studied, video stitching results are blurred and distorted, and limit the vertical expansion of monitoring range. And other issues

Pending Publication Date: 2021-01-12
CHINA UNIV OF MINING & TECH
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Problems solved by technology

[0005] The above methods have proposed certain technical improvements for underground video surveillance splicing, but there is no adaptive dynamic scheduling for the camera group used for underground monitoring, mainly for static targets or environmental monitoring scenarios, and for dynamic large targets (such as coal shearer

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  • Self-adaptive coal mining machine follow-up tracking multi-camera video splicing method
  • Self-adaptive coal mining machine follow-up tracking multi-camera video splicing method
  • Self-adaptive coal mining machine follow-up tracking multi-camera video splicing method

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Embodiment Construction

[0088] The structure and performance of the present invention will be further described below with reference to the accompanying drawings.

[0089] like Figure 1-12 As shown, the adaptive shearer tracking multi-camera video stitching method includes the following steps: manually marking the ROI (using a colored fluorescent band) at the central part of the shearer as the positioning anchor point of the camera calibration algorithm. The color component feature extraction algorithm is used to retrieve the ROI anchor points in the images collected by each camera, and at a certain algorithm time interval t q The ROI anchor point polling retrieval is performed on the video data of each camera in the order from left to right. If an anchor point is retrieved by one or several cameras, the subsequent cameras will stop retrieving. Then, according to the mapping relationship between the pixel coordinates and the real coordinates in the camera calibration, the camera group to be called ...

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Abstract

The invention discloses a self-adaptive coal mining machine follow-up tracking multi-camera video splicing method, belongs to the technical field of intelligent monitoring, and combines a camera groupself-adaptive follow-up tracking method with a coal mining machine video splicing algorithm to improve the splicing effect of coal mining machine monitoring videos under the condition of large parallax of a coal mining working face. The influence of monitoring dead angles of the cameras on the state monitoring of the coal mining machine is reduced; firstly, a colorful fluorescent band is used formarking the position of a machine body, and real space coordinates are obtained through a camera calibration principle; the cameras deployed on a coal mining working surface are activated in groups based on a camera group self-adaptive follow-up tracking method, and the currently activated camera group completes a video splicing task of a coal mining machine picture. The coal mining machine videosplicing algorithm comprises the following steps: splicing corresponding frame images of two monitoring videos by using an image splicing algorithm; screening SIFT feature points based on an RANSAC algorithm for registration of the two images; and finally, splicing the two images by searching for the optimal suture line, and thus large-range monitoring of operation of the coal mining machine is achieved.

Description

technical field [0001] The invention belongs to the technical field of intelligent monitoring, and relates to a multi-camera video splicing method for self-adaptive shearer tracking. Background technique [0002] As an important equipment for the mechanization and modernization of coal mine production, if the shearer fails, it will lead to the interruption of the entire coal mining face, and its operation status directly affects the safety production level and economic production efficiency of the coal mine. Because the shearer is a large and complex system integrating machinery, electricity and hydraulics, its body is very long, and it has problems such as high operational complexity and failure to detect work failures in time. The traditional video surveillance system cannot cover the entire body. It will produce monitoring blind spots and increase the failure rate of missed detection. [0003] Therefore, the fault monitoring system for large-scale shearers needs the coop...

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Application Information

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IPC IPC(8): G06T11/60G06T7/30G06T5/00G06K9/46
CPCG06T11/60G06T7/30G06T5/009G06T2207/10016G06V10/462
Inventor 董锴文孙彦景王博文周玉陈岩严云峰李媛媛
Owner CHINA UNIV OF MINING & TECH
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