Difference between quadtree and kd-tree

The difference (algorithmically) is: in quadtrees, the data reaching a node is split into a fixed (2^d), equal size cells, whereas in kdtrees, the data is split into two regions based on some data analysis (e.g. the median of some coordinate). Quadtrees do not scale well to high dimensions, due to the exponential dependency in … Read more

Quadtree for 2D collision detection

Your quadtree structure isn’t optimal. You’re right to store 4 subtrees per node, but actual objects should only be stored inside the leaves, not inner nodes. Therefore the collection holding the actual objects needs to be moved to the leaves. Let’s have a look at the implementation of the operations: Insert an object into the … Read more

R-Tree and Quadtree Comparison

Here’s paper which has pretty nice comparison of QuadTrees and R Trees: Quadtree and R-tree Indexes in Oracle Spatial: A Comparison using GIS Data Some differences: Quadtrees require fine-tuning by choosing appropriate tiling level in order to optimize performance. No specific tuning is required for R-Trees. Quadtree can be implemented on top of existing B-tree. … Read more

When to use Binary Space Partitioning, Quadtree, Octree?

There is no clear answer to your question. It depends entirely how your data is organized. Something to keep in mind: Quadtrees work best for data that is mostly two dimensional like map-rendering in navigation systems. In this case it’s faster than octrees because it adapts better to the geometry and keeps the node-structures small. … Read more

Efficient (and well explained) implementation of a Quadtree for 2D collision detection [closed]

Efficient Quadtrees All right, I’ll take a shot at this. First a teaser to show the results of what I’ll propose involving 20,000 agents (just something I whipped up real quick for this specific question): The GIF has extremely reduced frame rate and significantly lower res to fit the 2 MB maximum for this site. … Read more

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