EA-RAS: Towards Efficient and Accurate End-to-End Reconstruction of Anatomical Skeleton Article Swipe
Zhiheng Peng
,
Kai Zhao
,
Xiaoran Chen
,
Li Ma
,
Siyu Xia
,
Changjie Fan
,
Weijian Shang
,
Wei Jing
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2409.01555
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2409.01555
Efficient, accurate and low-cost estimation of human skeletal information is crucial for a range of applications such as biology education and human-computer interaction. However, current simple skeleton models, which are typically based on 2D-3D joint points, fall short in terms of anatomical fidelity, restricting their utility in fields. On the other hand, more complex models while anatomically precise, are hindered by sophisticate multi-stage processing and the need for extra data like skin meshes, making them unsuitable for real-time applications. To this end, we propose the EA-RAS (Towards Efficient and Accurate End-to-End Reconstruction of Anatomical Skeleton), a single-stage, lightweight, and plug-and-play anatomical skeleton estimator that can provide real-time, accurate anatomically realistic skeletons with arbitrary pose using only a single RGB image input. Additionally, EA-RAS estimates the conventional human-mesh model explicitly, which not only enhances the functionality but also leverages the outside skin information by integrating features into the inside skeleton modeling process. In this work, we also develop a progressive training strategy and integrated it with an enhanced optimization process, enabling the network to obtain initial weights using only a small skin dataset and achieve self-supervision in skeleton reconstruction. Besides, we also provide an optional lightweight post-processing optimization strategy to further improve accuracy for scenarios that prioritize precision over real-time processing. The experiments demonstrated that our regression method is over 800 times faster than existing methods, meeting real-time requirements. Additionally, the post-processing optimization strategy provided can enhance reconstruction accuracy by over 50% and achieve a speed increase of more than 7 times.
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- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2409.01555
- https://arxiv.org/pdf/2409.01555
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4402954835
All OpenAlex metadata
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- OpenAlex ID
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https://openalex.org/W4402954835Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2409.01555Digital Object Identifier
- Title
-
EA-RAS: Towards Efficient and Accurate End-to-End Reconstruction of Anatomical SkeletonWork title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-09-03Full publication date if available
- Authors
-
Zhiheng Peng, Kai Zhao, Xiaoran Chen, Li Ma, Siyu Xia, Changjie Fan, Weijian Shang, Wei JingList of authors in order
- Landing page
-
https://arxiv.org/abs/2409.01555Publisher landing page
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https://arxiv.org/pdf/2409.01555Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://arxiv.org/pdf/2409.01555Direct OA link when available
- Concepts
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End-to-end principle, Skeleton (computer programming), Dead end, Computer science, Anatomy, Artificial intelligence, Mathematics, Geometry, Biology, Flow (mathematics)Top concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.skeleton | 26, 101, 148, 186 |
| abstract_inverted_index.strategy | 160, 197, 232 |
| abstract_inverted_index.training | 159 |
| abstract_inverted_index.Efficient | 87 |
| abstract_inverted_index.arbitrary | 112 |
| abstract_inverted_index.education | 19 |
| abstract_inverted_index.estimates | 123 |
| abstract_inverted_index.estimator | 102 |
| abstract_inverted_index.fidelity, | 42 |
| abstract_inverted_index.leverages | 137 |
| abstract_inverted_index.precision | 206 |
| abstract_inverted_index.real-time | 77, 208, 226 |
| abstract_inverted_index.realistic | 109 |
| abstract_inverted_index.scenarios | 203 |
| abstract_inverted_index.skeletons | 110 |
| abstract_inverted_index.typically | 30 |
| abstract_inverted_index.Anatomical | 93 |
| abstract_inverted_index.Efficient, | 0 |
| abstract_inverted_index.End-to-End | 90 |
| abstract_inverted_index.Skeleton), | 94 |
| abstract_inverted_index.anatomical | 41, 100 |
| abstract_inverted_index.estimation | 4 |
| abstract_inverted_index.human-mesh | 126 |
| abstract_inverted_index.integrated | 162 |
| abstract_inverted_index.prioritize | 205 |
| abstract_inverted_index.processing | 63 |
| abstract_inverted_index.real-time, | 106 |
| abstract_inverted_index.regression | 215 |
| abstract_inverted_index.unsuitable | 75 |
| abstract_inverted_index.experiments | 211 |
| abstract_inverted_index.explicitly, | 128 |
| abstract_inverted_index.information | 8, 141 |
| abstract_inverted_index.integrating | 143 |
| abstract_inverted_index.lightweight | 194 |
| abstract_inverted_index.multi-stage | 62 |
| abstract_inverted_index.processing. | 209 |
| abstract_inverted_index.progressive | 158 |
| abstract_inverted_index.restricting | 43 |
| abstract_inverted_index.anatomically | 56, 108 |
| abstract_inverted_index.applications | 15 |
| abstract_inverted_index.conventional | 125 |
| abstract_inverted_index.demonstrated | 212 |
| abstract_inverted_index.interaction. | 22 |
| abstract_inverted_index.lightweight, | 97 |
| abstract_inverted_index.optimization | 167, 196, 231 |
| abstract_inverted_index.sophisticate | 61 |
| abstract_inverted_index.Additionally, | 121, 228 |
| abstract_inverted_index.applications. | 78 |
| abstract_inverted_index.functionality | 134 |
| abstract_inverted_index.plug-and-play | 99 |
| abstract_inverted_index.requirements. | 227 |
| abstract_inverted_index.single-stage, | 96 |
| abstract_inverted_index.Reconstruction | 91 |
| abstract_inverted_index.human-computer | 21 |
| abstract_inverted_index.reconstruction | 236 |
| abstract_inverted_index.post-processing | 195, 230 |
| abstract_inverted_index.reconstruction. | 187 |
| abstract_inverted_index.self-supervision | 184 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 8 |
| citation_normalized_percentile |