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Motion-estimation-based road video stabilization method

A technology for motion estimation and video stabilization, applied in digital video signal modification, television, computing, etc., to meet the requirements of road video surveillance, with good pertinence and improved image stabilization efficiency

Inactive Publication Date: 2011-09-28
CHANGAN UNIV +2
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  • Summary
  • Abstract
  • Description
  • Claims
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AI Technical Summary

Problems solved by technology

There are deficiencies in the existing motion estimation algorithms in practical applications, and it is necessary to study a motion estimation algorithm that can guarantee stable accuracy and have certain anti-interference ability in real-time video

Method used

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  • Motion-estimation-based road video stabilization method
  • Motion-estimation-based road video stabilization method
  • Motion-estimation-based road video stabilization method

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Embodiment Construction

[0022] The present invention will be further described below in conjunction with accompanying drawing. But the content of the present invention is not limited thereto.

[0023] The video stabilization system consists of four parts: image preprocessing, motion detection, motion filtering and motion compensation. Image preprocessing completes the removal of noise interference, retains the details of image content, and ensures the accuracy of image feature extraction; motion detection completes the detection of the relative motion vector between the camera system and the monitoring target, including motion estimation and motion decision-making; motion filtering passes Filter the motion parameters provided by the motion detection unit to distinguish between intentional motion and unintentional motion; motion compensation is to reorganize the image sequence through the motion parameters obtained after motion filtering, compensate for the image jitter between image frames, and compl...

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Abstract

The invention relates to a motion-estimation-based road video stabilization method, which comprises the following steps of: performing nonlinear smooth denoising on an input image; determining a characteristic searching range according to the requirements of a system on accuracy, and acquiring optimal characteristic information; performing cross grayscale projection on a template and a block to be matched, and finding an optimal matched area according to a difference; constructing a dynamic motion model in a recursion way by adopting a Kalman filter with a uniform motion equation, obtaining motion parameters of a camera for describing inter-frame motions caused by the motions of the camera, and identifying and filtering random jitter in an offset sequence obtained by motion estimation; and filling an area losing an image due to the video jitter, and reconstructing adjacent frames by adopting a hybrid Gaussian model and utilizing time relativity between image sequences.

Description

technical field [0001] The invention relates to a digital video stabilization method in a traffic video monitoring system, in particular to a road video stabilization method based on motion estimation. Background technique [0002] Automatic collection and processing of traffic flow parameter information is an important research topic in intelligent transportation system, and it is the basis of highway traffic management. It can be used to detect road traffic data such as traffic flow, vehicle type, vehicle speed, occupancy rate, etc. At the same time, it also counts relevant data for traffic management and provides effective digital basis for managers' decision-making. At present, traffic flow parameter detection is widely used in traffic guidance, road resource allocation, road construction evaluation and other fields. With the maturity of computer vision theory and vehicle recognition and traffic flow detection technology based on video acquisition equipment, the collec...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04N5/213H04N7/26G06T7/20H04N19/51
Inventor 李鹏孙大跃曹伟屈立成
Owner CHANGAN UNIV
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