The design of a texture display for three-dimensional Light Detection and Ranging (LiDAR) point clouds is investigated. The objective is to present a low fidelity display that is simple to compute in real-time, which utilizes the pattern processing capabilities of a human operator to afford an understanding of the environment. The efficacy of the display is experimentally evaluated by in comparison with a baseline point cloud rendering. Subjects were shown data based on virtual hills, and were asked to plan the least-steep traversal, and identify the hill from a set of distractors.
The major conclusions are: comprehension of LiDAR point clouds from the sensor origin is difficult without further processing of the data, a separated vantage point improves understanding of the data, and a simple computation to present local point cloud derivative data significantly improves the understanding of the environment, even when observed from the sensor origin.
| Identifer | oai:union.ndltd.org:TORONTO/oai:tspace.library.utoronto.ca:1807/32227 |
| Date | 21 March 2012 |
| Creators | Barbut, Ori |
| Contributors | Milgram, Paul |
| Source Sets | University of Toronto |
| Language | en_ca |
| Detected Language | English |
| Type | Thesis, Video |
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