SBIR Phase I: Exploiting High-Resolution Imagery, Geospatial Data, and Online Sources to Automatically Identify Direct Marketing Leads

SBIR 第一阶段：利用高分辨率图像、地理空间数据和在线资源自动识别直接营销线索

• 批准号: 0712287
• 负责人: Ching-Chien Chen
• 金额: --
• 依托单位: Geosemble Technologies, Inc.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-07-01 至 2008-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0712287&HistoricalAwards=false
• 关键词: SBIR; Phase; Exploiting; Resolution; Imagery

This Small Business Innovation Research Phase I project will conduct a feasibility study to demonstrate that by combining currently available high-resolution imagery, geospatial data (e.g., parcel data or structure data), and other related online data sources (e.g., property tax data or census data), it is possible to automatically generate highly targeted direct marketing leads for a variety of markets. The plan is to approach this problem by (1) aligning existing geospatial sources with the high-resolution imagery in order to determine the exact location and determine the address of the parcels seen in the imagery, (2) extracting the relevant features from the imagery to provide appropriate leads, such as determining the presence or absence of a swimming pool, the type of roofing materials used, or what types of cars are parked in the driveway, and (3) bringing in other sources of data, such as property tax assessment data to provide additional context. The primary focus of the phase I project will be to demonstrate the use of machine learning technology for identifying features in high-resolution imagery that can be used for direct marketing. High-resolution aerial imagery is now being widely collected and is available for low cost or in some cases is even free. The challenges are to first to align parcel data with the high resolution imagery to identify the exact address and boundaries of a property, and second to develop feature extraction techniques that can exploit the contextual information to accurately identify novel features, such as roofs, cars, pools, landscaping, etc., that can be used for direct marketing. The ability to accurately identify features in imagery and then relate them to specific properties as well as related sources of information will allow a targeted direct marketing product to be built. The end users of this product will be companies seeking to market products directly to residential consumers. This includes product and services relating to home improvement, both exterior and interior, as well as those products relating to residents of the home, that can be gleaned from imagery available for the parcel in question. This is a large market and includes everyone from home improvement stores to roofing companies, construction companies, automobile dealers, tree trimmers, landscapers, and pool construction companies. Beyond direct marketing, the technology can also be used for other applications that combine imagery, geospatial data, and structured information. For example, it could used for mosquito abatement, which is important to stop the spread of West Nile Virus, by identifying large pools of stagnant water, associating those hazards with the appropriate address, and then mailing abatement notifications to the residents.

这个小企业创新研究第一阶段项目将进行一项可行性研究，以证明通过结合目前可用的高分辨率图像、地理空间数据(例如，地块数据或结构数据)和其他相关的在线数据来源(例如，财产税数据或人口普查数据)，有可能自动为各种市场生成具有高度针对性的直接营销线索。计划通过(1)将现有地理空间来源与高分辨率图像对齐，以确定图像中看到的地块的确切位置和地址，(2)从图像中提取相关特征以提供适当的线索，例如确定游泳池的存在或不存在，所使用的屋顶材料的类型，或车道上停放的汽车类型，以及(3)引入其他数据来源，如财产税评估数据，以提供额外的背景。第一阶段项目的主要重点将是演示使用机器学习技术来识别可用于直接营销的高分辨率图像中的特征。高分辨率的航空图像现在被广泛收集，价格低廉，在某些情况下甚至是免费的。挑战是首先将地块数据与高分辨率图像对齐，以确定物业的确切地址和边界，其次开发特征提取技术，利用上下文信息准确识别可用于直接营销的新特征，如屋顶、汽车、游泳池、景观等。能够准确地识别图像中的特征，然后将它们与特定的属性以及相关的信息来源联系起来，这将使我们能够建立有针对性的直销产品。该产品的最终用户将是寻求直接向住宅消费者销售产品的公司。这包括与家庭装修有关的产品和服务，包括外部和内部，以及那些与家庭居民有关的产品，可以从有关地块的图像中收集到。这是一个巨大的市场，包括从家装商店到屋顶公司、建筑公司、汽车经销商、树木修剪师、园艺师和游泳池建筑公司的所有人。除了直接营销，这项技术还可以用于结合图像、地理空间数据和结构化信息的其他应用。例如，它可以用来减少蚊子，这对阻止西尼罗河病毒的传播非常重要，方法是识别大片积水，将这些危险与适当的地址联系起来，然后向居民邮寄消减通知。