自我中心数据中的自行车危险分类
Classifying Cycling Hazards in Egocentric Data
摘要：
这个建议是为创建和注释的一个以自我为中心的视频数据集的危险骑自行车的情况。由此产生的数据集将有助于改善骑自行车者的安全和体验的项目。由于骑自行车的人对路面状况和危险高度敏感，他们在导航路线时需要更多关于道路状况的细节。有轨电车轨道、鹅卵石、格栅和公用设施接入点等特征可能会对他们的旅程造成危险或不舒适的乘坐条件。该数据集的可能用途是为市政当局确定自行车基础设施中的现有危险，为骑自行车的人提供实时的危险和表面状况警告，以及确定导致骑自行车的人突然改变其直接路线的条件。
英文摘要：
This proposal is for the creation and annotation of an egocentric video data set of hazardous cycling situations. The resulting data set will facilitate projects to improve the safety and experience of cyclists. Since cyclists are highly sensitive to road surface conditions and hazards they require more detail about road conditions when navigating their route. Features such as tram tracks, cobblestones, gratings, and utility access points can pose hazards or uncomfortable riding conditions for their journeys. Possible uses for the data set are identifying existing hazards in cycling infrastructure for municipal authorities, real time hazard and surface condition warnings for cyclists, and the identification of conditions that cause cyclists to make sudden changes in their immediate route.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
