A real-time sampling method and system for mass data visualization

Abstract

This application belongs to the field of data processing technology and relates to a real-time sampling method and system for visualization of massive amounts of data, aiming to solve the problems of high computational load and low rendering performance when displaying massive spatial data in existing technologies. The method includes: constructing a three-dimensional spatial hierarchical data structure based on the spatial distribution of location data and dividing it into a screen space network; in each frame update, culling the data structure according to the camera's view frustum to obtain a set of nodes within the view frustum; establishing a mapping relationship between cells in the screen space network and nodes within the node set; assigning sampling indicators to each cell; and extracting the corresponding number of location data from the nodes corresponding to the cells with obtained sampling indicators according to the mapping relationship and performing coordinate transformation on them for display. This application, by combining spatial indexing and screen space division, strictly constrains the computational load of coordinate transformation within the upper limit of simultaneous display, improving the real-time sampling and rendering efficiency under large data volumes.

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