Panorama stitching method for removing moving object in moving video

Abstract

The invention relates to a panorama stitching method for removing a moving object in a moving video, comprising the following steps: (1) acquiring an appropriate number of video screenshots according to the length of a video, wherein the screenshot selection interval is shorter is the video is shorter, and the screenshot selection interval is longer if the video is longer; (2) projecting an original image to a sphere in order to prevent a final panorama from distortion and deformation; (3) carrying out SURF feature point detection on each frame of image to obtain a feature point description sub vector as the basis of matching; (4) carrying out feature point matching; (5) calculating a perspective (homographic) transformation matrix of every two frames of images based on matching feature points, and calculating forward and reverse homographic matrix transformation of two adjacent frames; (6) obtaining the size of the panorama based on the homographic transformation matrix of adjacent frames; and (7) inversely mapping the panorama to a sequence frame, building a candidate point list for each pixel point of the panorama, and removing a moving object, thus, completing generation of the panorama. The resolution of panorama generation is high, background overlay is accurate, and the 'ghost' phenomenon of the moving object is avoided.

Description

technical field [0001] The invention belongs to the field of video image processing, in particular to a panorama splicing method for removing moving objects in moving videos. Background technique [0002] Panorama stitching algorithm is one of the hot issues in image processing, no matter in academic field or engineering field. It has a large number of applications in various software, such as camera panorama synthesis and so on. The panorama is the scene that the observer can see from a fixed point of view, and it needs to express the complete real environment information. The synthesis of panoramas is prone to "ghosting", that is, there are multiple images of moving objects in the panorama, resulting in afterimages of moving objects at different times in the panorama, which affects the synthesis effect of the panorama. [0003] The current various algorithms still have defects, such as slow panorama synthesis, and tens of seconds of synthesis time for a 5-second video; ...

AI Technical Summary

Problems solved by technology

The synthesis of panoramas is prone to "ghosting", that is, there are multiple images of moving objects in the panorama, resulting in afterimages of moving objects at different times in the panorama, which affects the synthesis effect of the panorama

[0003] The current various algorithms still have defects, such as slow panorama synthesis, and tens of seconds of synthesis time for a 5-second video; It can move horizontally, but not vertically; moving objects are not completely eliminated, and there are afterimages, etc.

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