Objects are inserted into the quadtree based on their spatial locations, with the space being recursively divided into smaller quadrants. During collision detection, this structure allows for limiting checks to objects within the same or neighboring quadrants, significantly reducing the number of comparisons needed. Instead of checking every object against every other object, the quadtree confines these checks to localized regions, making the process much more efficient. By focusing computational resources on relevant areas where collisions are more likely to occur, quadtrees enable real-time collision detection, which is crucial for maintaining smooth interactions in applications such as video games, simulations, and virtual reality environments.
Here you can see the quadtree getting reconstructed every moment to update the positions of the objects. The colliding points are highlighted and this is achieved by checking every point for collision using quadtree, reducing the time complexity from O(n^2) to O(nlog(n)).
You can see the FPS has significantly increased. Warning: Do not stay in this page for too long.