- #1
phaothu365
- 2
- 0
Hi everyone,
I am new to computational geometry. As part of my master thesis, I have to solve a popular nearest neighbor problem. My task is to search for a point in a set of some 2000 4-dimensional points which is closest to a given point in the sense of Euclidean distance.
After reading some literatures and rich resources on Internet about this very well known NN problem, I found some helpful methods and variants to deal with it (linear search, space partitioning,e.t.c). However, my application is real time and thus requires fast computation such that the closest point is found as quickly as possible,i.e. search time is the most critical objective.
Can anyone who has experience in this fields suggest me some methods (in the vast quantity of methods available today) as optimal choices for my particular problem?
Thank you very much,
Regards,
Viet
I am new to computational geometry. As part of my master thesis, I have to solve a popular nearest neighbor problem. My task is to search for a point in a set of some 2000 4-dimensional points which is closest to a given point in the sense of Euclidean distance.
After reading some literatures and rich resources on Internet about this very well known NN problem, I found some helpful methods and variants to deal with it (linear search, space partitioning,e.t.c). However, my application is real time and thus requires fast computation such that the closest point is found as quickly as possible,i.e. search time is the most critical objective.
Can anyone who has experience in this fields suggest me some methods (in the vast quantity of methods available today) as optimal choices for my particular problem?
Thank you very much,
Regards,
Viet