Title: Audio-Based Pedestrian Detection in the Presence of Vehicular Noise Show Chinese title

Title: 基于音频的车辆噪声环境下的行人检测

Abstract: Audio-based pedestrian detection is a challenging task and has, thus far, only been explored in noise-limited environments. We present a new dataset, results, and a detailed analysis of the state-of-the-art in audio-based pedestrian detection in the presence of vehicular noise. In our study, we conduct three analyses: (i) cross-dataset evaluation between noisy and noise-limited environments, (ii) an assessment of the impact of noisy data on model performance, highlighting the influence of acoustic context, and (iii) an evaluation of the model's predictive robustness on out-of-domain sounds. The new dataset is a comprehensive 1321-hour roadside dataset. It incorporates traffic-rich soundscapes. Each recording includes 16kHz audio synchronized with frame-level pedestrian annotations and 1fps video thumbnails. Show Chinese abstract

Abstract: 基于音频的行人检测是一项具有挑战性的任务，迄今为止仅在噪声有限的环境中进行了探索。 我们提出一个新的数据集、结果以及在车辆噪声存在情况下基于音频的行人检测最新技术的详细分析。 在我们的研究中，我们进行了三项分析：(i) 在嘈杂环境和噪声有限环境之间的跨数据集评估，(ii) 对噪声数据对模型性能的影响进行评估，强调声学背景的影响，以及 (iii) 对模型在域外声音上的预测鲁棒性进行评估。 新数据集是一个全面的1321小时路边数据集。 它包含了交通丰富的声音场景。 每个录音包括与帧级行人注释同步的16kHz音频和1fps视频缩略图。