会员体验
专利管家(专利管理)
工作空间(专利管理)
风险监控(情报监控)
数据分析(专利分析)
侵权分析(诉讼无效)
联系我们
交流群
官方交流:
QQ群: 891211   
微信请扫码    >>>
现在联系顾问~
热词
    • 10. 发明专利
    • SYSTEM AND METHOD OF SOCIAL DISTANCING RECOGNITION IN CCTV SURVEILLANCE IMAGERY
    • CA3140898A1
    • 2022-06-02
    • CA3140898
    • 2021-12-02
    • PATRIOTONE TECH
    • SUAREZ GARCIA CESAR AUGUSTOCAMERON JAMES ALLAN DOUGLASMUNZ PHILLIP KONRAD
    • G06V20/52G06N20/00G06V20/40G06V40/10
    • A system and method for more accurate recognition of adherence to social distancing regulations in image data. A curated dataset of surveillance footage is used that shows people at a variety of angles at a wide variety of distances. The videos of this dataset are annotated and a second, numeric dataset is created as input into various classical machine learning models. The trained model is tested on more annotated data and shows a noticeable improvement over the other attempted methods. The resulting analytics allows for accurate distinction between pairs of people that are at least 6 feet apart and pairs of people that are not. This method utilizes a random forest machine learning model to improve on the Euclidean method that measures distance between human detection centroids in the 2-dimensional target image. A system and method for more accurate recognition of adherence to social distancing regulations in image data. A curated dataset of surveillance footage is used that shows people at a variety of angles at a wide variety of distances. The videos of this dataset are annotated and a second, numeric dataset is created as input into various classical machine learning models. The trained model is tested on more annotated data and shows a noticeable improvement over the other attempted methods. The resulting analytics allows for accurate distinction between pairs of people that are at least 6 feet apart and pairs of people that are not. This method utilizes a random forest machine learning model to improve on the Euclidean method that measures distance between human detection centroids in the 2-dimensional target image.