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Content Provider | ACM Digital Library |
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Author | Neumann, Ulrich Nocera, Luciano Gao, Zhenzhen |
Abstract | We present a scalable out-of-core technique for mapping colors from aerial oblique imagery to large scale aerial LiDAR (Light Detection and Ranging) point cloud. Our method does not require meshing or intensive processing of points, only fast and effective augmentation is applied to fill occluded points on building walls and under tree canopies. The presented system applies a modified visibility pass of GPU splatting to map colors, where occluded points are filtered out by projecting all points as oriented surface splats into images. A weighting scheme is utilized to accumulate colors from all contributing images while leveraging image resolution and surface orientation. The effectiveness of color mapping is demonstrated through visualizations of colored points by a GPU splatting algorithm. |
Starting Page | 426 |
Ending Page | 429 |
Page Count | 4 |
File Format | |
ISBN | 9781450316910 |
DOI | 10.1145/2424321.2424381 |
Language | English |
Publisher | Association for Computing Machinery (ACM) |
Publisher Date | 2012-11-06 |
Publisher Place | New York |
Access Restriction | Subscribed |
Subject Keyword | Aerial oblique imagery Augmentation Color mapping Visibility test Aerial lidar point cloud Gpu splatting Image blending Point-based rendering Texture mapping |
Content Type | Text |
Resource Type | Article |
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