Hierarchical voxel block hashing for efficient integration of depth images
Many modern 3D reconstruction methods accumulate information volumetrically using truncated signed distance functions. While this usually imposes a regular grid with fixed voxel size, not all parts of a scene necessarily need to be represented at the same level of detail. For example, a flat table n...
| Main Authors: | , , , |
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| Format: | Journal article |
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Institute of Electrical and Electronics Engineers
2015
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| _version_ | 1826275173182996480 |
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| author | Kahler, O Prisacariu, V Valentin, J Murray, D |
| author_facet | Kahler, O Prisacariu, V Valentin, J Murray, D |
| author_sort | Kahler, O |
| collection | OXFORD |
| description | Many modern 3D reconstruction methods accumulate information volumetrically using truncated signed distance functions. While this usually imposes a regular grid with fixed voxel size, not all parts of a scene necessarily need to be represented at the same level of detail. For example, a flat table needs less detail than a highly structured keyboard on it. We introduce a novel representation for the volumetric 3D data that uses hash functions rather than trees for accessing individual blocks of the scene, but which still provides different resolution levels. We show that our data structure provides efficient access and manipulation functions that can be very well parallelised, and also describe an automatic way of choosing appropriate resolutions for different parts of the scene. We embed the novel representation in a system for simultaneous localization and mapping from RGB-D imagery and also investigate the implications of the irregular grid on interpolation routines. Finally, we evaluate our system in experiments, demonstrating state-of-the-art representation accuracy at typical frame-rates around 100 Hz, along with 40% memory savings. |
| first_indexed | 2024-03-06T22:54:40Z |
| format | Journal article |
| id | oxford-uuid:5ff4d9a0-aa2b-47e9-91f1-0cd662d738c2 |
| institution | University of Oxford |
| last_indexed | 2024-03-06T22:54:40Z |
| publishDate | 2015 |
| publisher | Institute of Electrical and Electronics Engineers |
| record_format | dspace |
| spelling | oxford-uuid:5ff4d9a0-aa2b-47e9-91f1-0cd662d738c22022-03-26T17:50:21ZHierarchical voxel block hashing for efficient integration of depth imagesJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:5ff4d9a0-aa2b-47e9-91f1-0cd662d738c2Symplectic Elements at OxfordInstitute of Electrical and Electronics Engineers2015Kahler, OPrisacariu, VValentin, JMurray, DMany modern 3D reconstruction methods accumulate information volumetrically using truncated signed distance functions. While this usually imposes a regular grid with fixed voxel size, not all parts of a scene necessarily need to be represented at the same level of detail. For example, a flat table needs less detail than a highly structured keyboard on it. We introduce a novel representation for the volumetric 3D data that uses hash functions rather than trees for accessing individual blocks of the scene, but which still provides different resolution levels. We show that our data structure provides efficient access and manipulation functions that can be very well parallelised, and also describe an automatic way of choosing appropriate resolutions for different parts of the scene. We embed the novel representation in a system for simultaneous localization and mapping from RGB-D imagery and also investigate the implications of the irregular grid on interpolation routines. Finally, we evaluate our system in experiments, demonstrating state-of-the-art representation accuracy at typical frame-rates around 100 Hz, along with 40% memory savings. |
| spellingShingle | Kahler, O Prisacariu, V Valentin, J Murray, D Hierarchical voxel block hashing for efficient integration of depth images |
| title | Hierarchical voxel block hashing for efficient integration of depth images |
| title_full | Hierarchical voxel block hashing for efficient integration of depth images |
| title_fullStr | Hierarchical voxel block hashing for efficient integration of depth images |
| title_full_unstemmed | Hierarchical voxel block hashing for efficient integration of depth images |
| title_short | Hierarchical voxel block hashing for efficient integration of depth images |
| title_sort | hierarchical voxel block hashing for efficient integration of depth images |
| work_keys_str_mv | AT kahlero hierarchicalvoxelblockhashingforefficientintegrationofdepthimages AT prisacariuv hierarchicalvoxelblockhashingforefficientintegrationofdepthimages AT valentinj hierarchicalvoxelblockhashingforefficientintegrationofdepthimages AT murrayd hierarchicalvoxelblockhashingforefficientintegrationofdepthimages |