ASPED: An Audio Dataset for Detecting Pedestrians

Autor:	Seshadri, Pavan, Han, Chaeyeon, Koo, Bon-Woo, Posner, Noah, Guhathakurta, Subhrajit, Lerch, Alexander
Rok vydání:	2023
Předmět:	Electrical Engineering and Systems Science - Audio and Speech Processing Computer Science - Sound
Druh dokumentu:	Working Paper
Popis:	We introduce the new audio analysis task of pedestrian detection and present a new large-scale dataset for this task. While the preliminary results prove the viability of using audio approaches for pedestrian detection, they also show that this challenging task cannot be easily solved with standard approaches. Comment: 4+1 pages, ICASSP 2024
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2309.06531 Zobrazit plný text záznamu View this record from Arxiv