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WildPose: Long-Range 3D Motion Tracking of Cheetahs in the Wild Using Multi-Sensor Fusion
In many fields of research, it is often desirable to estimate the 3D pose of a subject - human, animal, or otherwise. Methods for obtaining accurate 3D pose data of a subject are broad in their applications; they inform the design of bio-mimetic robots, they aid greatly in bio-mechanical research, a...
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| Format: | Thesis |
| Language: | Eng |
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Department of Electrical Engineering
2024
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| _version_ | 1867613171083116544 |
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| access_status_str | Open Access |
| author | Joska, Daniel |
| author2 | Patel, Amir |
| author_browse | Joska, Daniel Patel, Amir |
| author_facet | Patel, Amir Joska, Daniel |
| author_sort | Joska, Daniel |
| collection | Thesis |
| description | In many fields of research, it is often desirable to estimate the 3D pose of a subject - human, animal, or otherwise. Methods for obtaining accurate 3D pose data of a subject are broad in their applications; they inform the design of bio-mimetic robots, they aid greatly in bio-mechanical research, and they are used commonly in the study of animal neuroscience. Currently, robust methods for long-range tracking of subjects in the wild are few and far between, given the rarity of specific training data as well as the generally challenging nature of the associated computer vision problems. This thesis describes the design, implementation, and testing of both a hardware and software component to a method for the 3D motion capture of cheetahs in the wild, dubbed WildPose. The method makes use of multi-sensor fusion including lidar, RGB and IMU sensors to compensate for situations where pure vision-based techniques perform inadequately. To increase robustness, the software design makes use of previously successful trajectory optimisation techniques to yield accurate pose data in adverse conditions that would otherwise be extremely difficult to obtain. The method is extendable to other species with minimal variations. We demonstrate the method's efficacy through experimental validation on challenging cheetah locomotion datasets collected in the wild, presenting both qualitative and quantitative analyses for varied movements, environments, and lighting conditions. Through the shown effectiveness of these techniques in our specific use case, we aim to prove that the methods used perform admirably even under the trickiest of reconstruction problems. Thereby, we present our findings on cheetahs as a promising blueprint for the 3D motion capture of other species. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/39568 |
| institution | University of Cape Town (South Africa) |
| language | Eng |
| last_indexed | 2026-06-10T12:31:53.390Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2024 |
| publishDateRange | 2024 |
| publishDateSort | 2024 |
| publisher | Department of Electrical Engineering |
| publisherStr | Department of Electrical Engineering |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/39568 WildPose: Long-Range 3D Motion Tracking of Cheetahs in the Wild Using Multi-Sensor Fusion Joska, Daniel Patel, Amir Engineering In many fields of research, it is often desirable to estimate the 3D pose of a subject - human, animal, or otherwise. Methods for obtaining accurate 3D pose data of a subject are broad in their applications; they inform the design of bio-mimetic robots, they aid greatly in bio-mechanical research, and they are used commonly in the study of animal neuroscience. Currently, robust methods for long-range tracking of subjects in the wild are few and far between, given the rarity of specific training data as well as the generally challenging nature of the associated computer vision problems. This thesis describes the design, implementation, and testing of both a hardware and software component to a method for the 3D motion capture of cheetahs in the wild, dubbed WildPose. The method makes use of multi-sensor fusion including lidar, RGB and IMU sensors to compensate for situations where pure vision-based techniques perform inadequately. To increase robustness, the software design makes use of previously successful trajectory optimisation techniques to yield accurate pose data in adverse conditions that would otherwise be extremely difficult to obtain. The method is extendable to other species with minimal variations. We demonstrate the method's efficacy through experimental validation on challenging cheetah locomotion datasets collected in the wild, presenting both qualitative and quantitative analyses for varied movements, environments, and lighting conditions. Through the shown effectiveness of these techniques in our specific use case, we aim to prove that the methods used perform admirably even under the trickiest of reconstruction problems. Thereby, we present our findings on cheetahs as a promising blueprint for the 3D motion capture of other species. 2024-05-02T09:15:09Z 2024-05-02T09:15:09Z 2023 2024-04-30T13:09:40Z Thesis / Dissertation Masters MSc http://hdl.handle.net/11427/39568 Eng application/pdf Department of Electrical Engineering Faculty of Engineering and the Built Environment |
| spellingShingle | Engineering Joska, Daniel WildPose: Long-Range 3D Motion Tracking of Cheetahs in the Wild Using Multi-Sensor Fusion |
| thesis_degree_str | Master's |
| title | WildPose: Long-Range 3D Motion Tracking of Cheetahs in the Wild Using Multi-Sensor Fusion |
| title_full | WildPose: Long-Range 3D Motion Tracking of Cheetahs in the Wild Using Multi-Sensor Fusion |
| title_fullStr | WildPose: Long-Range 3D Motion Tracking of Cheetahs in the Wild Using Multi-Sensor Fusion |
| title_full_unstemmed | WildPose: Long-Range 3D Motion Tracking of Cheetahs in the Wild Using Multi-Sensor Fusion |
| title_short | WildPose: Long-Range 3D Motion Tracking of Cheetahs in the Wild Using Multi-Sensor Fusion |
| title_sort | wildpose long range 3d motion tracking of cheetahs in the wild using multi sensor fusion |
| topic | Engineering |
| url | http://hdl.handle.net/11427/39568 |
| work_keys_str_mv | AT joskadaniel wildposelongrange3dmotiontrackingofcheetahsinthewildusingmultisensorfusion |