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Shortest Path Queries on Terrain Surfaces and Point Clouds
PhD Thesis Proposal Defence
Title: "Shortest Path Queries on Terrain Surfaces and Point Clouds"
by
Mr. Yinzhao YAN
Abstract:
Performing shortest path queries on a 3D surface has gained significant
attention from both industry and academia. Among different representations
of a 3D surface, the most popular representations are Triangular-Irregular
Network, i.e., TIN, and point cloud. However, all existing algorithms for
answering shortest path queries on a TIN are inefficient, and there is no
existing study focusing on answering shortest path queries directly on a
point cloud. In this thesis, we study how to effectively calculate the
shortest path passing on a TIN and a point cloud.
Firstly, we study shortest path queries on a weighted TIN using an
on-the-fly algorithm. Specifically, we propose an efficient
(1+epsilon)-approximate on-the-fly shortest path algorithm, that answers the
shortest path between two points passing different regions on a weighted
TIN, where different regions are assigned different weights. Our
experimental results show that it is up to 1,630 times and 40 times better
than the best-known algorithm on a weighted TIN in terms of the query time
and memory usage, with an error at most 1%, respectively.
Secondly, we study proximity queries, i.e., shortest path queries, k-Nearest
Neighbor (kNN) queries and range queries, on a point cloud using an oracle.
Specifically, we propose an efficient (1+epsilon)-approximate shortest path
oracle, that answers the shortest path query for a set of
Points-Of-Interests (POIs) on a point cloud. It can be easily adapted to the
case if POIs are not given as input. Then, we propose efficient algorithms
for answering the (1+epsilon)-approximate kNN and range query with the
assistance of our oracle. Our experimental results show that when POIs are
given (resp. not given) as input, our oracle is up to 390 times, 30 times
and 6 times (resp. 500 times, 140 times and 50 times) better than the
best-known adapted oracle (which is the oracle on a TIN) in terms of the
oracle construction time, oracle size and shortest path query time,
respectively. Our algorithms for the other two proximity queries are both up
to 100 times faster than the best-known adapted algorithm (which is the
algorithm on a TIN), with an error at most 8%, respectively.
Date: Wednesday, 26 February 2025
Time: 1:00pm - 3:00pm
Venue: Room 4472
Lifts 25/26
Committee Members: Prof. Raymond Wong (Supervisor)
Prof. Dimitris Papadias (Chairperson)
Prof. Pedro Sander
Prof. Xiaofang Zhou