Quick and automatic target detection method

Abstract

The invention mainly belongs to the technical field of target invasion detection and particularly relates to an unmanned aerial vehicle image-based region invasion target detection method. The method is used for target detection of an unmanned aerial vehicle. The method comprises the steps of performing Gaussian pyramid layering on an original image in an original video obtained by a vehicle-mounted camera of the unmanned aerial vehicle to lower calculation complexity of feature point extraction; and then extracting SIFT feature points of the image to perform image registration, capturing motion information in the image by adopting LK sparse optical flow of a pyramid to realize target point motion calculation, performing motion point clustering and false target removal, and finally performing target judgment to realize target detection. According to the method, the search range of inter-frame feature points of the unmanned aerial vehicle video can be reduced, the motion large-displacement problem in the unmanned aerial vehicle image is solved, and the detection capability is improved; and therefore, the manual detection intensity of region invasion is reduced and the automatic perception capability of the unmanned aerial vehicle is improved.

Description

technical field [0001] The invention mainly belongs to the technical field of target intrusion detection, and in particular relates to a target detection method for area intrusion based on unmanned aerial vehicle images. Background technique [0002] Target detection is the operation of separating the target of interest from the background area of ​​a single frame image or sequence image in a surveillance scene, and identifying and extracting meaningful object entities from the image. The prerequisite for UAVs to complete various tasks is to quickly and accurately detect targets in the surveillance scene. The current research on UAV moving target detection algorithms is in the stage of designing specific methods for specific problems, and the adaptability to complex and changeable working scenarios is poor. Also, the level of object detection required varies depending on the application environment. Generally speaking, the primary task of target detection is to search a ce...

AI Technical Summary

Problems solved by technology

For the video images obtained by the payload carried on the UAV, the continuity condition of optical flow is often not satisfied in time domain and air domain

Feature matching can only obtain the optical flow corresponding to the feature points in the local area, and cannot describe the overall motion displacement of the UAV video frame, and the calculation time is long

Images