Double-camera panoramic video splicing method based on suture line space-time optimization

Abstract

The invention relates to a video splicing method based on suture line space-time optimization and belongs to the field of video processing. The method comprises the following steps of detecting feature points through a SIFT algorithm and aligning the feature points, optimizing the feature points with RANSAC, and calculating the tie distance of the feature point pairs in the vertical direction, andpre-aligning a video frame; and based on a graph cutting algorithm, and constraints such as foreground, edge, parallax and the like, calculating the optimal suture line; smoothing the suture line sequence by means of the foreground detection and Gaussian filter; and performing quality evaluation on the suture line sequence; performing linear fusion on images on the two sides of the suture line byutilizing the quality of the suture line to obtain a panoramic video. Compared with methods in the prior art, the method reduces ghost images of the panoramic video, maintains the frame continuity ofthe video, and improves the visual quality of the video.

Description

technical field [0001] The invention relates to a video splicing method, in particular to a two-camera panoramic video splicing method based on the space-time optimization of suture lines, and belongs to the field of video processing. Background technique [0002] Due to the limitation of camera angle of view, traditional videos are shot within a certain range of angle of view. The viewer cannot see the scene outside the perspective. Different from traditional video, panoramic video can break the limitation of viewing angle and provide viewers with a full range of visual experience. Use a panoramic camera composed of multiple cameras to shoot real scenes, and then stitch and fuse multiple videos into one panoramic video. Users can wear a helmet-mounted display to watch panoramic videos, and interact with panoramic videos through head, body, gesture and other motion estimation to watch videos from different perspectives; they can also watch panoramic videos through smart te...

AI Technical Summary

Problems solved by technology

However, for video splicing, the transformation matrix of each frame is different, and the shape of the deformed image is quite different, which destroys the continuity between video frames.

And due to the lack of constraints on the edge and foreground, the seam calculated by this algorithm will pass through the object and the foreground, destroying the structure of the image

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