Moving object detection method based on expansion mixed gauss model

A mixed Gaussian model and moving target technology, applied in the field of pattern recognition, can solve the problems of poor results and improve the detection effect
CN101470809AInactive Publication Date: 2009-07-01INST OF AUTOMATION CHINESE ACAD OF SCI
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Patent Information

Authority / Receiving Office
CN ยท China
Patent Type
Applications(China)
Current Assignee / Owner
INST OF AUTOMATION CHINESE ACAD OF SCI
Publication Date
2009-07-01
Estimated Expiration
Not applicable ยท inactive patent

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Abstract

The invention relates to a motion target detecting method based on an expanded and mixed Gaussian model, wherein the method comprises the following steps: constructing a module through a first-level model, constructing probability density functions of shadow background and prospect based on the expanded and mixed Gaussian model, constructing a module through a second-level model, constructing probability density functions of motion targets and non-motion targets based on the three models, classifying through a classifying module and through applying a MAP-MRF(Maximum a Posteriori-Markov Random Field) method, applying feedback information which is traced, and further fining the prospect model. The motion target detecting method can overcome mistake detection of prospect caused by background motion through merging space information in the Gaussian mixed model, overcomes unbeneficial influence caused by shadows through merging background modeling, prospect detecting and shadow removing in a possibility framework, thereby improving the detection effect of a motion target.
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Description

technical field

[0001] The invention belongs to the field of pattern recognition, relates to technologies such as image processing and computer vision, and particularly relates to the detection of moving objects in video. Background technique

[0002] In the field of computer vision, one of the most fundamental problems is how to obtain high-level semantic understanding from the underlying raw video data. At present, the research on intelligent video surveillance at home and abroad mainly focuses on camera calibration, multi-camera fusion, and visual analysis of moving objects. Among them, the visual analysis of moving objects is one of the most active research topics in the field of computer vision. Its core is to use computer vision technology to detect, track and identify moving objects (such as people and cars, etc.) from image sequences and analyze their behavior. Understanding and description, it has broad application prospects in the fields of virtual reality, video ...

Claims

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