RealImpact: A Dataset of Impact Sound Fields for Real Objects

June 16, 2023 ยท Entered Twilight ยท ๐Ÿ› Computer Vision and Pattern Recognition

๐Ÿ’ค TWILIGHT: Eternal Rest
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Repo contents: .gitignore, LICENSE, README.md, dataset, hardware, microphone_visualization.ipynb, modes_dsp_sweep.ipynb, preprocess_annotations.py, preprocess_measurements.py, transform_obj.py

Authors Samuel Clarke, Ruohan Gao, Mason Wang, Mark Rau, Julia Xu, Jui-Hsien Wang, Doug L. James, Jiajun Wu arXiv ID 2306.09944 Category cs.SD: Sound Cross-listed cs.CV, cs.GR, eess.AS Citations 13 Venue Computer Vision and Pattern Recognition Repository https://github.com/samuel-clarke/RealImpact โญ 33 Last Checked 1 month ago
Abstract
Objects make unique sounds under different perturbations, environment conditions, and poses relative to the listener. While prior works have modeled impact sounds and sound propagation in simulation, we lack a standard dataset of impact sound fields of real objects for audio-visual learning and calibration of the sim-to-real gap. We present RealImpact, a large-scale dataset of real object impact sounds recorded under controlled conditions. RealImpact contains 150,000 recordings of impact sounds of 50 everyday objects with detailed annotations, including their impact locations, microphone locations, contact force profiles, material labels, and RGBD images. We make preliminary attempts to use our dataset as a reference to current simulation methods for estimating object impact sounds that match the real world. Moreover, we demonstrate the usefulness of our dataset as a testbed for acoustic and audio-visual learning via the evaluation of two benchmark tasks, including listener location classification and visual acoustic matching.
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