Metadata
Creators:
- Pausch, Florian
, Acoustics Research Institute
- Perfler, Felix
, Acoustics Research Institute
- Holighaus, Nicki
, Acoustics Research Institute
- Majdak, Piotr
, Acoustics Research Institute
Publishers:
Rightsholders:
Keywords:
- Human adult pinna
- Physically based modeling
- Parametric pinna model
- BezierPPM
- Machine-learning algorithm
- Artificial intelligence (AI)
Relations:
- Mesh2PPM 1.0.0: Training is referenced by the Tool Mesh2PPM 1.0.0 (2022-2024).
- Mesh2PPM 1.0.0: Training was created with the Tool PyBezierPPM 3.0 (2024).
- Mesh2PPM 1.0.0: Training can be processed by the Tool Mesh2PPM 1.0.0 (2022-2024).
- Mesh2PPM 1.0.0: Training is supplement to the Tool Mesh2PPM 1.0.0 (2022-2024).
- Mesh2PPM 1.0.0: Training requires https://developer.blender.org/docs/release_notes/4.1/ (URL).
- Mesh2PPM 1.0.0: Training requires https://www.python.org/downloads/release/python-3110/ (URL).
Other:
- DOI: not assigned yet
- Uploaded by: Florian Pausch
- Date (created): 2025-06-30 12:35:37 (GMT)
- Date (updated): 2025-10-15 10:54:30 (GMT)
- Production Year: 2022-2024
- Resource Type: Dataset (SONICOM Ecosystem)
- Rights: EUPL-1.2: European Union Public Licence version 1.2
- Subject Areas: Life Science , Other SONICOM Ecosystem
- General Description: Database of synthetic pinna meshes and BezierPPM parameters used to train Mesh2PPM, a AI-based estimator of pinna parameters from meshes.
- Technical Remarks: Contains BezierPPM parameters (CSV files), BezierPPM instances rendered as meshes (STL files), these meshes rendered as multi-view grey-scale images (PNG files) and depth images (OpenEXR files). For rendering, the camera perspectives were either set to nominal (No Jitter) or small variation from nominal (Jitter).
- Data Source: Computer simulated
Comments
1 comments found:- Florian Pausch (2025-06-30 13:06:49): The Database Mesh2PPM 1.0.0: Training will be published upon manuscript publication.
Uploaded by: Florian Pausch
Created: 2025-06-30 12:35:37
Updated: 2025-10-15 10:54:30