百度地图用街景自动验证海量地点信息,效率提升50倍。
DuMapper: Towards Automatic Verification of Large-Scale POIs with Street Views at Baidu Maps
- 利用街景图像和坐标生成向量,快速匹配数据库中的地点信息。
- 系统上线3.5年完成超4亿次验证,相当于800名专家工作量。
- 适合地图维护、自动化地理信息验证等场景的从业者参考。
随着移动设备普及,网络地图服务已成为日常必需。为保障位置搜索等服务体验,点位信息(POI)数据库作为核心基础设施,存储了与人们生活密切相关的数十亿个地理实体信息,如商店、银行等。因此,大规模验证POI数据准确性至关重要。目前工业界普遍采用众包地理信息(VGI)平台,依赖成千上万的众包人员和专业测绘员进行验证,但每年需投入数百万美元人力成本。为降低开支,我们提出DuMapper,一个基于百度地图街景数据的全自动大规模POI验证系统。该系统输入街景招牌图像与地理坐标,生成低维向量,借助近似最近邻(ANN)算法在数亿条已存POI中实现毫秒级精准匹配。该系统使验证吞吐量提升50倍。自部署以来,已持续运行于 exttt{DuMPOnline},显著提升百度地图的验证效率。截至2021年12月31日,系统累计完成超过4.05亿次验证迭代,相当于约800名高性能专家的总工作量。
原文摘要 · Abstract (English)
With the increased popularity of mobile devices, Web mapping services have become an indispensable tool in our daily lives. To provide user-satisfied services, such as location searches, the point of interest (POI) database is the fundamental infrastructure, as it archives multimodal information on billions of geographic locations closely related to people's lives, such as a shop or a bank. Therefore, verifying the correctness of a large-scale POI database is vital. To achieve this goal, many industrial companies adopt volunteered geographic information (VGI) platforms that enable thousands of crowdworkers and expert mappers to verify POIs seamlessly; but to do so, they have to spend millions of dollars every year. To save the tremendous labor costs, we devised DuMapper, an automatic system for large-scale POI verification with the multimodal street-view data at Baidu Maps. DuMapper takes the signboard image and the coordinates of a real-world place as input to generate a low-dimensional vector, which can be leveraged by ANN algorithms to conduct a more accurate search through billions of archived POIs in the database for verification within milliseconds. It can significantly increase the throughput of POI verification by $50$ times. DuMapper has already been deployed in production since \DuMPOnline, which dramatically improves the productivity and efficiency of POI verification at Baidu Maps. As of December 31, 2021, it has enacted over $405$ million iterations of POI verification within a 3.5-year period, representing an approximate workload of $800$ high-performance expert mappers.
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