A method for accelerating the decoding of camera video streams through programmable gpu in a virtual-real fusion system

Abstract

The invention discloses a method for accelerating the decoding of a camera video stream by a programmable GPU in a virtual-real fusion system, comprising: obtaining original YUV video; creating a single-channel texture from the pixel stream of each frame of YUV picture and transmitting it to the GPU; drawing a three-dimensional virtual scene, and judging Whether the current pixel belongs to the camera image; RGB pixels are mixed with the 3D scene to form the final virtual-real fusion image. Compared with the traditional method of decoding YUV video pixels in multiple threads on the CPU, the present invention can effectively cut more original video pixels that do not need sampling, and at the same time, based on the GPU with stronger parallel decoding capability, the decoding efficiency can be greatly improved. The algorithm of the invention is clear and the result is robust, and the method can be used in the fusion application of large-scale three-dimensional virtual scene and real-time monitoring, and can be used in good combination with the current mainstream camera manufacturer's video.

Description

technical field [0001] The invention relates to the optimization of camera video decoding efficiency in a virtual-real fusion system, in particular to a method for accelerating the decoding of a camera video stream through a programmable GPU in the virtual-real fusion system. Background technique [0002] With the rapid development of "smart cities", the coverage density and construction quality of video surveillance systems in public areas have been greatly improved. At present, the most commonly used solution for various monitoring command centers is the monitoring video wall. Every time the monitoring personnel see the video screen, they need to understand the scene in their brains. From a cognitive point of view, frequently shifting their attention will cause the feedback time to increase and Brain fatigue. By 3D modeling of the environment in which the camera is deployed, the surveillance video of the 2D screen is seamlessly integrated into the 3D scene. Such a virtua...

AI Technical Summary

Problems solved by technology

[0003] The drawing of 3D virtual scenes will have high requirements for efficiency, and the operations of video transmission, recognition, decoding, transcoding and so on will also bring great pressure to the hardware

However, the high compression ratio also brings high algorithm complexity and a large amount of calculation. If the CPU is used for decoding, it will occupy a large amount of CPU computing resources.

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