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
    • 7. 发明授权
    • Self learning face recognition using depth based tracking for database generation and update
    • 使用基于深度的跟踪来进行数据库生成和更新的自学习人脸识别
    • US08855369B2
    • 2014-10-07
    • US13530925
    • 2012-06-22
    • Harshavardhana Narayana KikkeriMichael F. KoenigJeffrey Cole
    • Harshavardhana Narayana KikkeriMichael F. KoenigJeffrey Cole
    • G06K9/00
    • G06K9/00926G06K9/00221G06K9/00248G06K9/00295G06K9/00369G06T2207/10016
    • Face recognition training database generation technique embodiments are presented that generally involve collecting characterizations of a person's face that are captured over time and as the person moves through an environment, to create a training database of facial characterizations for that person. As the facial characterizations are captured over time, they are will represent the person's face as viewed from various angles and distances, different resolutions, and under different environmental conditions (e.g., lighting and haze conditions). Further, over a long period of time where facial characterizations of a person are collected periodically, these characterizations can represent an evolution in the appearance of the person. This produces a rich training resource for use in face recognition systems. In addition, since a person's face recognition training database can be established before it is needed by a face recognition system, once employed, the training will be quicker.
    • 提出了面部识别训练数据库生成技术实施例,其通常涉及收集随时间被捕获的人的脸部的特征,以及当人们通过环境移动时,为该人创建面部表征的训练数据库。 随着随着时间的流逝捕获面部特征,它们将代表从各种角度和距离,不同分辨率以及在不同环境条件(例如,照明和阴霾条件)下观察的人脸。 此外,在长时间地定期收集人的面部特征的时候,这些表征可以代表人的外观的演变。 这为人脸识别系统提供了丰富的培训资源。 另外,由于人脸识别训练数据库可以在人脸识别系统需要之前建立,所以一旦使用,训练就会更快。