AUTOMATED GENERATION OF HIGH-QUALITY 3D POINT CLOUDS OF ANTLERS USING LOW-COST RANGE CAMERAS
Three-dimensional imaging demonstrates advantages over traditional methods and has already proven feasible for measuring antler growth. However, antlers' velvet-covered surface and irregular structure pose challenges in efficiently obtaining high-quality antler data. Animal data capture using o...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2022-05-01
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| Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B2-2022/531/2022/isprs-archives-XLIII-B2-2022-531-2022.pdf |
| _version_ | 1818213698356903936 |
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| author | S. Cheng D. D. Lichti J. Matyas |
| author_facet | S. Cheng D. D. Lichti J. Matyas |
| author_sort | S. Cheng |
| collection | DOAJ |
| description | Three-dimensional imaging demonstrates advantages over traditional methods and has already proven feasible for measuring antler growth. However, antlers' velvet-covered surface and irregular structure pose challenges in efficiently obtaining high-quality antler data. Animal data capture using optical imaging devices and point cloud segmentation still require tedious manual work. To obtain 3D data of irregular biological targets like antlers, this paper proposes an automated workflow of high-quality 3D antler point cloud generation using low-cost range cameras. An imaging system of range cameras and one RGB camera is developed for automatic camera triggering and data collection without motion artifacts. The imaging system enables motion detection to ensure data collection occurs without any appreciable animal movement. The antler data are extracted automatically based on a fast k-d tree neighbor search to remove the irrelevant data. Antler point clouds from different cameras captured with various poses are aligned using target-based registration and the normal distribution transformation (NDT). The two-step registration demonstrates precisions of the overall RMSE of 4.8mm for the target-based method and Euclidean fitness score of 10.5mm for the NDT. Complete antler point clouds are generated with a higher density than that of individual frames and improved quality with outliers removed. |
| first_indexed | 2024-12-12T06:08:25Z |
| format | Article |
| id | doaj.art-a4c67872a44d4cc883253131de3daf68 |
| institution | Directory Open Access Journal |
| issn | 1682-1750 2194-9034 |
| language | English |
| last_indexed | 2024-12-12T06:08:25Z |
| publishDate | 2022-05-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| spelling | doaj.art-a4c67872a44d4cc883253131de3daf682022-12-22T00:35:14ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342022-05-01XLIII-B2-202253153810.5194/isprs-archives-XLIII-B2-2022-531-2022AUTOMATED GENERATION OF HIGH-QUALITY 3D POINT CLOUDS OF ANTLERS USING LOW-COST RANGE CAMERASS. Cheng0D. D. Lichti1J. Matyas2Dept. of Geomatics Engineering, University of Calgary, Calgary, AB, CanadaDept. of Geomatics Engineering, University of Calgary, Calgary, AB, CanadaDept. of Comparative Biology & Experimental Medicine, University of Calgary, Calgary, AB, CanadaThree-dimensional imaging demonstrates advantages over traditional methods and has already proven feasible for measuring antler growth. However, antlers' velvet-covered surface and irregular structure pose challenges in efficiently obtaining high-quality antler data. Animal data capture using optical imaging devices and point cloud segmentation still require tedious manual work. To obtain 3D data of irregular biological targets like antlers, this paper proposes an automated workflow of high-quality 3D antler point cloud generation using low-cost range cameras. An imaging system of range cameras and one RGB camera is developed for automatic camera triggering and data collection without motion artifacts. The imaging system enables motion detection to ensure data collection occurs without any appreciable animal movement. The antler data are extracted automatically based on a fast k-d tree neighbor search to remove the irrelevant data. Antler point clouds from different cameras captured with various poses are aligned using target-based registration and the normal distribution transformation (NDT). The two-step registration demonstrates precisions of the overall RMSE of 4.8mm for the target-based method and Euclidean fitness score of 10.5mm for the NDT. Complete antler point clouds are generated with a higher density than that of individual frames and improved quality with outliers removed.https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B2-2022/531/2022/isprs-archives-XLIII-B2-2022-531-2022.pdf |
| spellingShingle | S. Cheng D. D. Lichti J. Matyas AUTOMATED GENERATION OF HIGH-QUALITY 3D POINT CLOUDS OF ANTLERS USING LOW-COST RANGE CAMERAS The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| title | AUTOMATED GENERATION OF HIGH-QUALITY 3D POINT CLOUDS OF ANTLERS USING LOW-COST RANGE CAMERAS |
| title_full | AUTOMATED GENERATION OF HIGH-QUALITY 3D POINT CLOUDS OF ANTLERS USING LOW-COST RANGE CAMERAS |
| title_fullStr | AUTOMATED GENERATION OF HIGH-QUALITY 3D POINT CLOUDS OF ANTLERS USING LOW-COST RANGE CAMERAS |
| title_full_unstemmed | AUTOMATED GENERATION OF HIGH-QUALITY 3D POINT CLOUDS OF ANTLERS USING LOW-COST RANGE CAMERAS |
| title_short | AUTOMATED GENERATION OF HIGH-QUALITY 3D POINT CLOUDS OF ANTLERS USING LOW-COST RANGE CAMERAS |
| title_sort | automated generation of high quality 3d point clouds of antlers using low cost range cameras |
| url | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B2-2022/531/2022/isprs-archives-XLIII-B2-2022-531-2022.pdf |
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