Parallel simplification and compression of reality captured models
Reality capture technologies such as laser scanner and photogrammetry are becoming more democratize day-by-day, as such we are currently undergoing an influx of high-resolution photo-realistic 3D models that contain ever-increasing geometric and texture details and resolution. The massive data file...
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | Thesis-Master by Research |
| Language: | English |
| Published: |
Nanyang Technological University
2020
|
| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/136785 |
| _version_ | 1826113882335215616 |
|---|---|
| author | Koh, Naimin |
| author2 | Zheng Jianmin |
| author_facet | Zheng Jianmin Koh, Naimin |
| author_sort | Koh, Naimin |
| collection | NTU |
| description | Reality capture technologies such as laser scanner and photogrammetry are becoming more democratize day-by-day, as such we are currently undergoing an influx of high-resolution photo-realistic 3D models that contain ever-increasing geometric and texture details and resolution. The massive data file size required to store this information can cause difficulty for both the transfer and manipulation of the captured model. This problem is even more prevalent for mobile or handheld capture devices with limited available internal disk space on the device itself.
The three main outputs of a complete reality capture pipeline are dense point cloud, 3d mesh model and texture maps. To reduce the size of each of these outputs, we employ data compression and simplification techniques while striving to retain as much quality as possible. Given the large initial input size and expected long processing time, we explored specifically parallel algorithms in order to fully utilize modern multi-core CPU and GPU to accelerate the computation.
This thesis focuses on the parallelized simplification and compression algorithm for large-scale point cloud, 3D mesh, and textures. These input models are generated from running the full reconstruction of a photogrammetry 3D reconstruction pipeline. We have investigated and proposed parallelizable methods to reduce file size for each of the output types while still managed to retain high visual quality like the raw captures. |
| first_indexed | 2024-10-01T03:30:30Z |
| format | Thesis-Master by Research |
| id | ntu-10356/136785 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T03:30:30Z |
| publishDate | 2020 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1367852020-10-28T08:29:18Z Parallel simplification and compression of reality captured models Koh, Naimin Zheng Jianmin School of Computer Science and Engineering asjmzheng@ntu.edu.sg Engineering::Computer science and engineering::Computing methodologies::Computer graphics Reality capture technologies such as laser scanner and photogrammetry are becoming more democratize day-by-day, as such we are currently undergoing an influx of high-resolution photo-realistic 3D models that contain ever-increasing geometric and texture details and resolution. The massive data file size required to store this information can cause difficulty for both the transfer and manipulation of the captured model. This problem is even more prevalent for mobile or handheld capture devices with limited available internal disk space on the device itself. The three main outputs of a complete reality capture pipeline are dense point cloud, 3d mesh model and texture maps. To reduce the size of each of these outputs, we employ data compression and simplification techniques while striving to retain as much quality as possible. Given the large initial input size and expected long processing time, we explored specifically parallel algorithms in order to fully utilize modern multi-core CPU and GPU to accelerate the computation. This thesis focuses on the parallelized simplification and compression algorithm for large-scale point cloud, 3D mesh, and textures. These input models are generated from running the full reconstruction of a photogrammetry 3D reconstruction pipeline. We have investigated and proposed parallelizable methods to reduce file size for each of the output types while still managed to retain high visual quality like the raw captures. Master of Engineering 2020-01-24T04:40:11Z 2020-01-24T04:40:11Z 2019 Thesis-Master by Research Koh, N. (2019). Parallel simplification and compression of reality captured models. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/136785 10.32657/10356/136785 en This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0). application/pdf Nanyang Technological University |
| spellingShingle | Engineering::Computer science and engineering::Computing methodologies::Computer graphics Koh, Naimin Parallel simplification and compression of reality captured models |
| title | Parallel simplification and compression of reality captured models |
| title_full | Parallel simplification and compression of reality captured models |
| title_fullStr | Parallel simplification and compression of reality captured models |
| title_full_unstemmed | Parallel simplification and compression of reality captured models |
| title_short | Parallel simplification and compression of reality captured models |
| title_sort | parallel simplification and compression of reality captured models |
| topic | Engineering::Computer science and engineering::Computing methodologies::Computer graphics |
| url | https://hdl.handle.net/10356/136785 |
| work_keys_str_mv | AT kohnaimin parallelsimplificationandcompressionofrealitycapturedmodels |