Image rendering method and related device

Abstract

The embodiment of the present application discloses an image rendering method and a related device, wherein the method includes: acquiring texture data corresponding to the particle road map, the texture data includes texel data corresponding to each road section in the particle road map, and the texel data is used for To carry the position data of the reference sampling point on the corresponding road section, the reference sampling point is obtained by sampling the particle trajectory supported by the road section based on the reference frame rate; when rendering each frame of the particle road map, for the particle road map For each particle, according to the animation running time corresponding to the picture, based on the texel data corresponding to the road section to which the particle belongs in the texture data, determine the position data of the particle at the animation running time; The position data when the animation is running, and render the frame in the particle road map. The embodiments of the present application can be applied to the map field and the traffic field, and can reduce CPU computing overhead and improve rendering efficiency of particle traffic maps.

Description

technical field [0001] The present application relates to the field of maps, in particular to an image rendering method and related devices. Background technique [0002] The particle road map is a visualization scheme that simulates vehicles with dynamic particles and reflects road traffic conditions through the moving speed, moving direction, color and density of particles. In practical applications, if the particle traffic map is to achieve the effect of particle flow, it is necessary to continuously redraw the rendering of the particle traffic map at a certain frame rate, and update the position of the particles in each frame. [0003] In related technologies, before redrawing and rendering the picture of the particle road map, it is necessary to traverse all the particles in the particle road map, and perform geometric operations on all the particles, so as to determine the update position data of all particles in the next frame of the picture. [0004] In the face of ...

AI Technical Summary

Problems solved by technology

[0004] In the face of a large number of particles in the particle road map, the above position update calculation is performed before each rendering of the particle road map, which will bring a very large computational overhead to the central processing unit (CPU).

Moreover, the CPU also needs to transmit the updated position data of all the particles it calculates to the graphics processing unit (GPU), so that the GPU can render the next frame of the particle traffic map based on the updated position data of all particles. Due to the required transmission The amount of data is large, so the above data transmission process usually results in a long transmission time, which will also affect the rendering efficiency of the particle road map

Images