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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