Low latency photon mapping using block hashing
Proceedings of the ACM SIGGRAPH/EUROGRAPHICS conference on Graphics hardware
Interactive global illumination using fast ray tracing
EGRW '02 Proceedings of the 13th Eurographics workshop on Rendering
Spatial queries in wireless broadcast systems
Wireless Networks - Special issue: Pervasive computing and communications
Direct segmentation of algebraic models for reverse engineering
Computing - Geometric modelling dagstuhl 2002
An Improved Evolutionary Approach for Egomotion Estimation with a 3D TOF Camera
IWINAC '09 Proceedings of the 3rd International Work-Conference on The Interplay Between Natural and Artificial Computation: Part II: Bioinspired Applications in Artificial and Natural Computation
| Hi-index | 0.00 |
The problem of k-nearest neighbors computation within a 3D data set is frequently encountered in Computer Graphics. Applications include the technique of photon-map rendering where the closest photons to a given one have to be identified and the segmentation phase within a reverse engineering process. In this paper we present a new algorithm for k-nearest neighbors computation based on median subdivision and a hashing strategy. The major advantage of our hashing function is that bounds can be established that limit the number of points to be inspected during the search process. Estimates for the asymptotic complexity of our search method are given. Finally we compare our algorithm with a different search strategy based on KD-Trees.