The invention discloses a real-time stitching method for a high-definition video. The method mainly comprises the following steps of synchronous video decoding, initialization, frame-by-frame stitching and the like. Firstly, a high-definition original video of a network camera is collected, and the video is synchronously decoded. For a first frame of video image, the initialization is carried outand includes the steps of video registration based on sub-regions, finding of an optimal stitching line set, generation of a look-up table and the like. After the initialization is completed, the frame-by-frame stitching is carried out and includes the steps of coordinate mapping of video images, detection of a moving object, stitching line update, video fusion and the like, and finally a stitchedvideo is output. In addition, a parallelization strategy is adopted for each step in video decoding and frame-by-frame stitching stages. According to the method, the real-time requirement of high-definition video stitching can be met, and a stitching frame rate is not less than 30 fps for a double-path 720P video; and meanwhile, the phenomena of ghosting, blurring, exposure inconsistence and thelike in the stitched video are avoided.

Real-time stitching method for high-definition video

The embodiment of the invention discloses a video stitching method and apparatus The method comprises the following steps: when a to-be-processed video frame is a specific video frame, using an image overlapping area between the to-be-processed video frame and an adjacent video frame corresponding to the to-be-processed video frame as a ROI video image; performing significant area detection on the ROI video image, performing feature point detection on the significant area by using the SURF algorithm, and performing rough matching on feature points by using the nearest neighbor and next nearest neighbor ratio algorithm; purifying the feature points subjected to the rough matching by using the RANSAC algorithm, and calculating a projection transformation matrix corresponding to the feature points; and fusing and stitching the to-be-processed video frame and the adjacent video frame by using the projection transformation matrix to obtain a target video frame According to the above operation manner, the detection efficiency and the matching accuracy of the feature points of the video frame are improved, and the requirements of video stitching for a real-time processing speed are satisfied

Video stitching method and apparatus

An apparatus and method for efficient image optimized image stitching. For example, one embodiment of an apparatus comprises: feature search area identification circuitry/logic to narrow down a feature search area based on possible overlap between two image frames; feature detection circuitry/logic to identify a plurality of feature points in a first image frame of the two image frames; feature matching circuitry/logic to map one or more of the plurality of feature points from the first image frame to corresponding feature points in the right image frame; image frame stitching and blending circuitry/logic to stitch the first image frame and second image frame based on the mapping of the feature points between the two image frames and to blend a portion of the first image frame with a portion of the second image frame.

Apparatus and method for optimized image stitching based on optical flow

The invention discloses a method for splicing videos in real time and belongs to technical field of video image processing. The method computes the overlapped area of video frame images to be spliced by using a phase correlation method, improves a SURF (Speeded UP Robust Features) algorithm, simplifies the generation process of a characteristic point descriptor in the SURF algorithm, reduces the dimensionality of the descriptor, extracts the characteristic points of the overlapped area of the video frames by using the improved SURF algorithm. The invention provides an image registration method based on characteristic block matching to match the characteristic points, decrease calculated amount, increase computational efficiency, and quickly solve an image conversion model by using the characteristic block matching. Finally the invention provides a projection matrix updating method based on a correlation coefficient. The projection matrix updating method is used for updating a projection matrix, prevents erroneous splicing results, and fusing the video frame images so as to splice the videos in real time.

Zhou Yan

Papers

Method for splicing videos in real time based on SURF (Speeded UP Robust Features) algorithm