EVALUATING MONOCULAR DEPTH ESTIMATION METHODS
Depth estimation from monocular images has become a prominent focus in photogrammetry and computer vision research. Monocular Depth Estimation (MDE), which involves determining depth from a single RGB image, offers numerous advantages, including applications in simultaneous localization and mapping...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2023-10-01
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| Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://isprs-archives.copernicus.org/articles/XLVIII-1-W3-2023/137/2023/isprs-archives-XLVIII-1-W3-2023-137-2023.pdf |
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| author | N. Padkan N. Padkan P. Trybala R. Battisti F. Remondino C. Bergeret C. Bergeret |
| author_facet | N. Padkan N. Padkan P. Trybala R. Battisti F. Remondino C. Bergeret C. Bergeret |
| author_sort | N. Padkan |
| collection | DOAJ |
| description | Depth estimation from monocular images has become a prominent focus in photogrammetry and computer vision research. Monocular Depth Estimation (MDE), which involves determining depth from a single RGB image, offers numerous advantages, including applications in simultaneous localization and mapping (SLAM), scene comprehension, 3D modeling, robotics, and autonomous driving. Depth information retrieval becomes especially crucial in situations where other sources like stereo images, optical flow, or point clouds are not available. In contrast to traditional stereo or multi-view methods, MDE techniques require fewer computational resources and smaller datasets. This research work presents a comprehensive analysis and evaluation of some state-of-the-art MDE methods, considering their ability to infer depth information in terrestrial images. The evaluation includes quantitative assessments using ground truth data, including 3D analyses and inference time. |
| first_indexed | 2024-03-11T17:18:33Z |
| format | Article |
| id | doaj.art-5f3dea78fb07427eb2dc443d1437b8ef |
| institution | Directory Open Access Journal |
| issn | 1682-1750 2194-9034 |
| language | English |
| last_indexed | 2024-03-11T17:18:33Z |
| publishDate | 2023-10-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| spelling | doaj.art-5f3dea78fb07427eb2dc443d1437b8ef2023-10-19T18:11:36ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342023-10-01XLVIII-1-W3-202313714410.5194/isprs-archives-XLVIII-1-W3-2023-137-2023EVALUATING MONOCULAR DEPTH ESTIMATION METHODSN. Padkan0N. Padkan1P. Trybala2R. Battisti3F. Remondino4C. Bergeret5C. Bergeret63D Optical Metrology (3DOM) unit, Bruno Kessler Foundation (FBK), Trento, ItalyDept. Mathematics, Computer Science and Physics, University of Udine, Italy3D Optical Metrology (3DOM) unit, Bruno Kessler Foundation (FBK), Trento, Italy3D Optical Metrology (3DOM) unit, Bruno Kessler Foundation (FBK), Trento, Italy3D Optical Metrology (3DOM) unit, Bruno Kessler Foundation (FBK), Trento, Italy3D Optical Metrology (3DOM) unit, Bruno Kessler Foundation (FBK), Trento, ItalyENSG, Paris, FranceDepth estimation from monocular images has become a prominent focus in photogrammetry and computer vision research. Monocular Depth Estimation (MDE), which involves determining depth from a single RGB image, offers numerous advantages, including applications in simultaneous localization and mapping (SLAM), scene comprehension, 3D modeling, robotics, and autonomous driving. Depth information retrieval becomes especially crucial in situations where other sources like stereo images, optical flow, or point clouds are not available. In contrast to traditional stereo or multi-view methods, MDE techniques require fewer computational resources and smaller datasets. This research work presents a comprehensive analysis and evaluation of some state-of-the-art MDE methods, considering their ability to infer depth information in terrestrial images. The evaluation includes quantitative assessments using ground truth data, including 3D analyses and inference time.https://isprs-archives.copernicus.org/articles/XLVIII-1-W3-2023/137/2023/isprs-archives-XLVIII-1-W3-2023-137-2023.pdf |
| spellingShingle | N. Padkan N. Padkan P. Trybala R. Battisti F. Remondino C. Bergeret C. Bergeret EVALUATING MONOCULAR DEPTH ESTIMATION METHODS The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| title | EVALUATING MONOCULAR DEPTH ESTIMATION METHODS |
| title_full | EVALUATING MONOCULAR DEPTH ESTIMATION METHODS |
| title_fullStr | EVALUATING MONOCULAR DEPTH ESTIMATION METHODS |
| title_full_unstemmed | EVALUATING MONOCULAR DEPTH ESTIMATION METHODS |
| title_short | EVALUATING MONOCULAR DEPTH ESTIMATION METHODS |
| title_sort | evaluating monocular depth estimation methods |
| url | https://isprs-archives.copernicus.org/articles/XLVIII-1-W3-2023/137/2023/isprs-archives-XLVIII-1-W3-2023-137-2023.pdf |
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