Accelerating kd-tree Searches for all k-nearest Neighbours

Merry, Bruce and Gain, James and Marais, Patrick (2013) Accelerating kd-tree Searches for all k-nearest Neighbours, Proceedings of 34th Annual Conference of the European Association for Computer Graphics (Eurographics 2013), 6-10 May 2013, Girona, Spain.

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Finding the k nearest neighbours of each point in a point cloud forms an integral part of many point-cloud processing tasks. One common approach is to build a kd-tree over the points and then iteratively query the k nearest neighbors of each point. We introduce a simple modification to these queries to exploit the coherence between successive points; no changes are required to the kd-tree data structure. The path from the root to the appropriate leaf is updated incrementally, and backtracking is done bottom-up. We show that this can reduce the time to compute the neighbourhood graph of a 3D point cloud by over 10%, and by up to 24% when k = 1. The gains scale with the depth of the kd-tree, and the method is suitable for parallel implementation.

Item Type: Conference paper
Additional Information: The definitive version is available at
Uncontrolled Keywords: kd-tree, nearest neighbours
Subjects: Computing methodologies > Computer graphics
Alternate Locations:;internal&action=action.digitallibrary.ShowPaperAbstract
Date Deposited: 30 Oct 2013
Last Modified: 10 Oct 2019 15:33

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