method for accelerating decoding of a camera video stream through a programmable GPU in a virtual-real fusion system

Abstract

The invention discloses a method for accelerating decoding of a camera video stream through a programmable GPU in a virtual-real fusion system. The method comprises the steps of obtaining an originalYUV video; Creating a single-channel texture for the pixel flow of each frame of YUV image and transmitting the single-channel texture to the GPU; Drawing a three-dimensional virtual scene, and judging whether the current pixel belongs to a camera image or not; And mixing the RGB pixels and the three-dimensional scene to form a final virtual-real fusion image. Compared with a traditional method for decoding YUV video pixels on a CPU in a multi-thread mode, more original video pixels which do not need to be sampled can be effectively cut, and meanwhile the decoding efficiency is greatly improved on the basis of a GPU with higher parallel decoding capacity. The method is clear in algorithm and robust in result, can be applied to fusion application of a large three-dimensional virtual scene and real-time monitoring, and can be well combined with a video of a current mainstream camera manufacturer for use.

Description

technical field [0001] The invention relates to the optimization of video decoding efficiency of a camera in a virtual-real fusion system, in particular to a method for accelerating decoding of a video stream of a camera through a programmable GPU in a 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 and 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, frequent diversion of attention will result in longer feedback time and Brain fatigue. Through the three-dimensional modeling of the environment where the camera is deployed, the surveillance video of the two-dimensional picture is seamlessly integrated...

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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