The invention discloses a method for extracting spatial information based on a
spiking neural network, and relates to the technical field of 3D
point cloud processing, and the method comprises the specific steps: firstly collecting 3D
point cloud original data, and obtaining effective data through denoising and coordinate
standardization; inputting a pulse space position coding layer, and generating pulse features containing local details by using an
algorithm; dividing a feature map according to spatial sub-regions and maintaining a
state vector; inputting a dynamic event coding layer, detecting correlation, triggering connection, and adjusting weight to realize global fusion; and finally, outputting by an output layer, providing spatial information for subsequent tasks, and completing extraction. According to the method, the 3D point space position is accurately represented through pulse coding,
local topology details are mined, and accurate local
information support is provided; and through a
mutual information entropy dynamic weight rendering mechanism, global space context efficient transmission fusion is realized, local and global conditions are considered, the method adapts to complex scenes, comprehensive and reliable support is provided for space calculation tasks, and the
processing effect is improved.