I\'m using OpenCL to find the nearest neighbour between two set of 3D points. Nearest Neighbour: For each point(x,y,z) in the DataSet I have to find the nearest one in the model. Squared distance = (
I am writing a method that takes as input an array of points and finds, for each point in the array, the closest point to it other than itself. I am currently doing this in a brute force way (cheking
I\'m implementing a KD-tree to cluster points a map into groups. I\'ve been using Wikipedia\'s KD-tree article as a reference. The search returns the correct nearest neighbor point, but it is slower t
I have a collection of n dimensional points and I want to find which 2 are the closest. The best I could come up for 2 dimensions is:
So I\'m trying to find details about an algorithm by Michael Rabin, which finds the nearest-neighbor given a set of points in 2D in O(n) time. For some reason, google searc开发者_运维技巧h is complete
Say I have a huge (a few million) list of n vectors, given a new vec开发者_如何学运维tor, I need to find a pretty close one from the set but it doesn\'t need to be the closest. (Nearest Neighbor finds
I think I know how to do K-Nearest-Neighbors using Cover Trees. (Incidentally: can anybody point me to a run-time complexity analysis of this?),开发者_如何学JAVA BUT I am looking for all-kNN (that is:
Given a quaternion value, I开发者_开发技巧 would like to find its nearest neighbour in a set of quaternions. To do this, I clearly need a way to compare the \"distance\" between two quaternions. What
If one wanted to perform the K-nearest-neighbors algorithm to do classification on im开发者_如何学Pythonages, how are features extracted from the images?What are the easiest, most effective methods?Gr
While working on the simulation of particle interactions, I stumbled across grid indexing in Morton-order (Z-order)(Wikipedia link) which is regarded to provide an efficient nearest neighbor cell sear
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