Listen to Your Map: An Online Representation for Spatial Sonification
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
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2024
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| _version_ | 1866910912926973952 |
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| author | Wu, Lan Jin, Craig Uttsha, Monisha Mushtary Vidal-Calleja, Teresa |
| author_facet | Wu, Lan Jin, Craig Uttsha, Monisha Mushtary Vidal-Calleja, Teresa |
| contents | Robotic perception is becoming a key technology for navigation aids, especially helping individuals with visual impairments through spatial sonification. This paper introduces a mapping representation that accurately captures scene geometry for sonification, turning physical spaces into auditory experiences. Using depth sensors, we encode an incrementally built 3D scene into a compact 360-degree representation with angular and distance information, aligning this way with human auditory spatial perception. The proposed framework performs localisation and mapping via VDB-Gaussian Process Distance Fields for efficient online scene reconstruction. The key aspect is a sensor-centric structure that maintains either a 2D-circular or 3D-cylindrical raster-based projection. This spatial representation is then converted into binaural auditory signals using simple pre-recorded responses from a representative room. Quantitative and qualitative evaluations show improvements in accuracy, coverage, timing and suitability for sonification compared to other approaches, with effective handling of dynamic objects as well. An accompanying video demonstrates spatial sonification in room-like environments. https://tinyurl.com/ListenToYourMap |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2412_05486 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Listen to Your Map: An Online Representation for Spatial Sonification Wu, Lan Jin, Craig Uttsha, Monisha Mushtary Vidal-Calleja, Teresa Robotics Robotic perception is becoming a key technology for navigation aids, especially helping individuals with visual impairments through spatial sonification. This paper introduces a mapping representation that accurately captures scene geometry for sonification, turning physical spaces into auditory experiences. Using depth sensors, we encode an incrementally built 3D scene into a compact 360-degree representation with angular and distance information, aligning this way with human auditory spatial perception. The proposed framework performs localisation and mapping via VDB-Gaussian Process Distance Fields for efficient online scene reconstruction. The key aspect is a sensor-centric structure that maintains either a 2D-circular or 3D-cylindrical raster-based projection. This spatial representation is then converted into binaural auditory signals using simple pre-recorded responses from a representative room. Quantitative and qualitative evaluations show improvements in accuracy, coverage, timing and suitability for sonification compared to other approaches, with effective handling of dynamic objects as well. An accompanying video demonstrates spatial sonification in room-like environments. https://tinyurl.com/ListenToYourMap |
| title | Listen to Your Map: An Online Representation for Spatial Sonification |
| topic | Robotics |
| url | https://arxiv.org/abs/2412.05486 |