Adaptive Context-Based Systems for Face Recognition in Video Surveillance
Adaptive Context-Based Systems for Face Recognition in Video Surveillance
批准号:
RGPIN-2016-06783
负责人:
Granger, Eric
金额:
$1.89万
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2017
资助国家:
加拿大
项目状态:
已结题
起止时间:
2017-01-01 至 2018-12-31
中文摘要
静止到视频人脸识别(FR)是视频监控中的一项重要功能,通过摄像机网络捕获的人脸与参考静止图像进行匹配。目前,最先进的系统的性能受到多个非静态操作环境的严重影响,这些非静态操作环境由例如姿势、照明和摄像机视点的变化定义。此外,由于个人通常使用在注册期间捕获的一张或几张参考剧照来注册,因此人脸模型通常不能很好地代表要在操作期间识别的人脸。
英文摘要
Still-to-video face recognition (FR) is an important function in video surveillance, where faces captured across a network of video cameras are matched against reference stills images. Currently, the performance of state-of-the-art systems is severely affected by the multiple non-stationary operational environments, defined by variations in, e.g., pose, illumination and camera viewpoint. Moreover, since an individual is typically enrolled using one or few reference stills captured during enrolment, face models are often poor representatives of the faces to be recognized during operations.
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