Vibe and disparity map background subtraction method-based moving target detection method

Abstract

The invention discloses a Vibe and disparity map background subtraction method-based moving target detection method, and relates to the field of computer vision. The method comprises the steps of firstly building a Gaussian model according to a disparity map sequence, and performing moving target detection by adopting a disparity map background subtraction method; secondly performing moving targetdetection based on an improved Vibe algorithm; and finally performing AND operation on two moving target detection results to obtain a final moving target region, continuing to update a background model, and performing moving target detection of the next frame. A monocular vision-based target detection method and a binocular vision-based target detection method are combined; the complete moving target can be extracted; the problem that the monocular vision-based moving target detection is easily influenced by lighting and shadows is improved; and the ghost phenomenon can be eliminated.

Description

technical field [0001] The invention relates to the field of computer vision, in particular to a moving target detection method based on Vibe and disparity map background difference method. Background technique [0002] Moving target detection is the basis of target recognition and tracking. Fast and accurate detection of moving targets is conducive to follow-up work such as target tracking, recognition and behavior understanding. It has a wide range of applications in iris, face recognition, security monitoring, robot navigation, aircraft and satellite monitoring systems, etc. [0003] Among them, there are three kinds of moving target detection algorithms: optical flow method, frame difference method and background difference method. The optical flow method requires special hardware support, and the calculation is complex and computationally intensive, so it is generally seldom used. The principle of the inter-frame difference method is simple, and it is not sensitive to...

AI Technical Summary

Problems solved by technology

The optical flow method requires special hardware support, and the calculation is complex and computationally intensive, so it is generally less used

The principle of the inter-frame difference method is simple and insensitive to noise and light changes, but the target detection results are prone to holes

The background difference method can extract the complete information of the target, but it is easily affected by the dynamic changes of the external scene such as lighting

When the moving object changes slowly to fast motion, the background difference method can easily detect the background exposed area (that is, the current background still has the moving object information of the previous frame, but the moving object is no longer in this area) as the foreground. The phenomenon of "shadow" appears, and the noise processing effect is not good in complex scenes such as tree branches swinging, and the adaptability to the environment is poor. Such false detections will cause difficulties in subsequent target tracking.

The traditional moving target detection method based on monocular vision can detect the outline of the moving target, but it is easily affected by external conditions, and will detect shadows and part of the background as foreground

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