人体位置に頑健な音響ベース3次元人体姿勢推定
Acoustic-based 3D Human Pose Estimation Robust to Human Position
低レベル音響信号のみから3次元人体姿勢を推定する際、従来法は対象者がスピーカーとマイクの直線上にいることを暗黙に仮定していた。本研究では位置判別器と残響耐性モデルを組み合わせ、多様な位置に対応できる手法を提案し、データセット構築と実験で有効性を示した。
著者: Yusuke Oumi, Yuto Shibata, Go Irie, Akisato Kimura, Yoshimitsu Aoki, Mariko Isogawa
分類: cs.SD, cs.AI, cs.CV, cs.LG, cs.RO
原文アブストラクト
This paper explores the problem of 3D human pose estimation from only low-level acoustic signals. The existing active acoustic sensing-based approach for 3D human pose estimation implicitly assumes that the target user is positioned along a line between loudspeakers and a microphone. Because reflection and diffraction of sound by the human body cause subtle acoustic signal changes compared to sound obstruction, the existing model degrades its accuracy significantly when subjects deviate from this line, limiting its practicality in real-world scenarios. To overcome this limitation, we propose a novel method composed of a position discriminator and reverberation-resistant model. The former predicts the standing positions of subjects and applies adversarial learning to extract subject position-invariant features. The latter utilizes acoustic signals before the estimation target time as references to enhance robustness against the variations in sound arrival times due to diffraction and reflection. We construct an acoustic pose estimation dataset that covers diverse human locations and demonstrate through experiments that our proposed method outperforms existing approaches.
