Multi-view Video Splicing System

In traditional video surveillance systems, supervisors need to watch multiple surveillance images at the same time. Surveillance video resources are scattered and huge, making it difficult to browse them all and extract useful information from them in a timely manner. The video splicing system can be used to merge multiple images and splice and fuse images from different perspectives to form a whole image, which is convenient for personnel supervision. This article introduces a multi-view video splicing system: it consists of several video cameras. Through the GStreamer framework, video streaming is performed in real time and the pictures are transmitted into the video fusion system. In the system, SURF feature points are extracted from several pictures to simulate After the radial transformation, real-time splicing is performed on them. After comparing the APAP algorithm, Multi Blend algorithm, Stitching algorithm, and the best fusion line algorithm, the best fusion line algorithm is selected for video fusion. At the same time, considering that the system requires a large amount of data operations, if the CPU is simply used to process too many videos, the effect of the algorithm and the delay of the video are often unsatisfactory. The system uses CUDA to combine the SURF algorithm and image simulation. The radial transformation is performed on the GPU, which greatly improves the fusion effect and speed of the video. Through experiments, the system can complete the splicing task better. At the same time, compared with not using CUDA for acceleration, the frame rate is increased from 3 frames per second to 25 frames, and the display can basically achieve real-time effects.