5 September 2014 High-performance meshing processing of remote sensing data on large displays
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Visualizing light detection and ranging (LIDAR) scans consisting of millions of points on large displays poses a significant challenge. High-resolution large displays allow researchers to examine point clouds in detail. However, how to interact with point clouds rendered on large displays is a difficult problem. We present a case study that visualizes LIDAR point clouds on a tiled display wall termed highly interactive-parallelized display (HIPerDisplay). It has twenty 24-inch liquid-crystal displays with a total resolution of 46 Mpixels. Interaction between the user and the display wall is achieved by using a video camera system that is able to track the position of a hand-held light ball device. A user holds it to manipulate point clouds on the HIPerDisplay. Case studies are conducted to study the LIDAR scans of slopes in the Houshanyue mountain areas in Taiwan. Experiments were conducted to examine the advantages of using the HIPerDisplay for point clouds in data postprocessing. The experiments assess two tasks for manipulating point cloud data designed to evaluate the efficiency of the interactive devices. To evaluate the efficiency of the system, a group of 30 graduate students participated in the experiment. User surveys were performed to evaluate the efficiency of the system and to discover the users’ opinions about using the interactive device in a large display environment. The results showed that the participants preferred to perform LIDAR data operation tasks on a high-resolution large display environment rather than on a single monitor. The results also showed that the HIPerDisplay offered superior performance for the processing of large LIDAR datasets.
© 2014 Society of Photo-Optical Instrumentation Engineers (SPIE)
Tung-Ju Hsieh, Wei-Yao Chen, Che-Hao Chang, Yen-Lin Chen, Ming-Li Lin, Shih-Ching Yeh, Yang-Lang Chang, Bormin Huang, "High-performance meshing processing of remote sensing data on large displays," Journal of Applied Remote Sensing 8(1), 084796 (5 September 2014). https://doi.org/10.1117/1.JRS.8.084796

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