ViLMA
+ Non-redundant data structures :
Point cloud data used by ViLMA are pre-processed and stored in non-redundant data structures, reducing storage requirements on both client and server sides and leveraging network traffic.
+ Multi-resolution out-of-core point cloud rendering :
ViLMA implements techniques such as dynamic point size, eye-dome lighting and multi-resolution out-of-core structures in order to render realistic point clouds with billions of points.
+ Low RAM and VRAM consumption :
The use of non-redundant data structures in addition to fixed-size GPU buffers allow ViLMA to achieve low RAM and VRAM consumption, which is especially relevant when running in browsers with security memory limits or devices with moderate amounts of memory.
+ Measurements and filtering :
The design of ViLMA is focused on providing useful measurement tools and visualization options. Point clouds can be rendered and filtered based on several LiDAR properties and distances, areas or volumes (among others) can be measured directly over the images.
