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Adhered crowd segmenting and tracking methods based on superpixel and graph model

A superpixel segmentation and superpixel technology, applied in image analysis, image data processing, instruments, etc., can solve the problems of inaccurate segmentation of human targets, cumbersome installation and debugging, inaccurate data, etc., to achieve good segmentation results and improve accuracy. , to achieve the effect of precise positioning

Inactive Publication Date: 2013-06-19
ZHEJIANG UNIV
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  • Summary
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  • Claims
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AI Technical Summary

Problems solved by technology

This method has disadvantages such as high cost and cumbersome installation and debugging in practical application.
[0011] Therefore, in view of the above-mentioned defects in the current prior art, it is necessary to conduct research to provide a solution to solve the defects in the prior art, avoiding the inability to accurately segment the human body object, and the data provided by subsequent data processing is not accurate. precise

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  • Adhered crowd segmenting and tracking methods based on superpixel and graph model
  • Adhered crowd segmenting and tracking methods based on superpixel and graph model
  • Adhered crowd segmenting and tracking methods based on superpixel and graph model

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Embodiment Construction

[0038] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0039] On the contrary, the invention covers any alternatives, modifications, equivalent methods and schemes within the spirit and scope of the invention as defined by the claims. Further, in order to make the public have a better understanding of the present invention, some specific details are described in detail in the detailed description of the present invention below. The present invention can be fully understood by those skilled in the art without the description of these detailed parts.

[0040] refer to figure 1, which is a flowchart of a method for segmenting and tracking cohesive crowd...

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Abstract

The embodiment of the invention discloses adhered crowd segmenting and tracking methods based on superpixel and a graphical model. The methods are used for segmenting and tracking target crowded people and have high robustness and adaptability, the outline of each target can be accurately extracted, and clear data can be provided for subsequent data processing. The methods comprise the following steps of: performing target detection and tracking on an initially input video image to obtain head position information, such as a motion foreground, of each target; performing superpixel pre-segmentation on the motion foreground to acquire a foreground superpixel segmentation image; and constructing the weighted graph model on the foreground superpixel segmentation image according to prior shape information and color information of human bodies, and finding out optimal segmentation borders among the adhered targets by finding the optimal path.

Description

technical field [0001] The invention belongs to the technical field of image digital processing, in particular to a method for segmenting and tracking cohesive crowds based on superpixels and graph models. Background technique [0002] In recent years, with the rapid growth of the national economy, the rapid progress of society and the continuous enhancement of comprehensive national strength, the demand for safety precautions and on-site recording and alarm systems in the fields of banking, electric power, transportation, security inspection and military facilities is increasing day by day, and the requirements are becoming more and more serious. High, video surveillance has been widely used in all aspects of production and life. The video surveillance system that needs manual monitoring has shown its inadaptability in many aspects. If you want to quickly find the desired content in the massive video data, you need to waste a lot of human resources, and when the operator co...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06T7/20
Inventor 于慧敏蔡丹平
Owner ZHEJIANG UNIV
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