用手机实时采集无障碍道路数据，让普通人也能参与城市地图更新
iOSPointMapper: RealTime Pedestrian and Accessibility Mapping with Mobile AI
- 用iPhone/iPad的摄像头和LiDAR在本地完成语义分割与深度估计
- 检测交通标志、信号灯、杆件等路侧设施，定位精度达厘米级
- 用户可验证数据并匿名上传，适合城市规划者与残障群体使用
精准且实时的人行道数据对建设无障碍、包容性步行基础设施至关重要，但当前数据采集方式往往成本高、碎片化且难以扩展。我们提出iOSPointMapper，一款基于移动端的实时、隐私保护式人行道测绘应用，利用最新款iPhone和iPad实现地面实时测绘。系统结合设备端语义分割、基于LiDAR的深度估计以及融合的GPS/IMU数据，检测并定位交通标志、信号灯、电杆等与人行道相关的关键要素。为确保透明度与数据质量，iOSPointMapper提供用户引导的标注界面，在提交前验证系统输出。采集数据经匿名化处理后传输至交通数据交换倡议（TDEI），可无缝融入多模态交通数据集。系统在特征检测与空间定位性能方面的详细评估表明其在提升行人地图质量方面的潜力。整体方案提供了一种可扩展、以用户为中心的方法，有效填补行人基础设施数据空白。
原文摘要 · Abstract (English)
Accurate, up-to-date sidewalk data is essential for building accessible and inclusive pedestrian infrastructure, yet current approaches to data collection are often costly, fragmented, and difficult to scale. We introduce iOSPointMapper, a mobile application that enables real-time, privacy-conscious sidewalk mapping on the ground, using recent-generation iPhones and iPads. The system leverages on-device semantic segmentation, LiDAR-based depth estimation, and fused GPS/IMU data to detect and localize sidewalk-relevant features such as traffic signs, traffic lights and poles. To ensure transparency and improve data quality, iOSPointMapper incorporates a user-guided annotation interface for validating system outputs before submission. Collected data is anonymized and transmitted to the Transportation Data Exchange Initiative (TDEI), where it integrates seamlessly with broader multimodal transportation datasets. Detailed evaluations of the system's feature detection and spatial mapping performance reveal the application's potential for enhanced pedestrian mapping. Together, these capabilities offer a scalable and user-centered approach to closing critical data gaps in pedestrian
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