Moving object detection method based on Gaussian mixture model and superpixel segmentation

A hybrid Gaussian model and superpixel segmentation technology, applied in image analysis, image enhancement, image data processing, etc., can solve problems such as complex scenes, unsatisfactory effects, ignoring the spatial correlation between pixels and pixels, and eliminate the interference of shadows , The detection method is accurate and real-time

Inactive Publication Date: 2016-04-27
SHANGHAI INST OF TECH
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Problems solved by technology

The disadvantage is that the spatial correlation between pixels is ignored, the more complex the scene, the less ideal the effect

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  • Moving object detection method based on Gaussian mixture model and superpixel segmentation
  • Moving object detection method based on Gaussian mixture model and superpixel segmentation
  • Moving object detection method based on Gaussian mixture model and superpixel segmentation

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Embodiment Construction

[0030] The present invention will be described in detail below in conjunction with accompanying drawings and specific embodiments, figure 1 The flow chart of the inventive method in this paper is shown, and then the implementation details of each step are specifically introduced.

[0031] Step 1: Build a real-time background model;

[0032] In the video image sequence, each frame image contains R, G, B color information. The background model is to describe the characteristics of pixel i at time t.

[0033] x i,t =[R i,t ,G i,t ,B i,t ]

[0034] Where i, t represent natural numbers;

[0035] If no moving object exists, the image to be detected is relatively still. The change of each pixel satisfies a certain mathematical model. The method uses a mixture model of M Gaussian distributions to identify each pixel, and the k-th order Gaussian probability density function

[0036] η k ( X ...

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Abstract

The invention discloses a moving object detection method based on a Gaussian mixture model and superpixel segmentation. The task of moving object detection is extracting objects of interest as many as possible from a complex scene and presenting the results in the form of binary images. The method is characterized by, to begin with, carrying out background modeling by utilizing the Gaussian mixture model and obtaining a background image of the current frame; then, carrying out superpixel segmentation on the current frame through an SLIC(simple linear iterative clustering) algorithm; and finally, carrying out LTP (local ternary pattern) texture feature extraction on the segmented images and background images, and then, carrying out comparison to obtain a moving object. The beneficial effects of the method are that the method can detect the moving object in real time according to the video images captured by cameras; and the detection method is efficient and accurate.

Description

technical field [0001] The invention belongs to the field of intelligent video monitoring and relates to a video moving target detection algorithm, in particular to a moving target detection method based on a mixed Gaussian model and superpixel segmentation. Background technique [0002] In the past ten years, with the gradual improvement of public security awareness, the technology in the field of intelligent monitoring has made great progress, and it has begun to be more and more applied in the fields of security, transportation and the Internet. Moving object detection combines computer vision and pattern recognition technology, and is one of the most basic and core research directions in intelligent video surveillance systems. [0003] Image segmentation refers to dividing an image into several relatively independent regions. Because image processing is mostly performed at the pixel level, if pixels with the same characteristics can be segmented out, the complexity of s...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06T7/20
CPCG06T2207/10016
Inventor 陈颖董嘉炜宗盖盖
Owner SHANGHAI INST OF TECH
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