基于人脸识别的数字视频监控系统由于具有隐蔽性、非接触性等优势，近年来得到了广泛关注。
The video surveillance system based on face recognition has the advantage of concealment and non-contact, so it has received extensive attention in recent years.
与此同时，在计算机视觉、模式识别和多媒体技术等研究领域中，人脸作为图像与视频中的视觉对象之一，占有非常重要的地位。
Meanwhile human face as the visual object of images and videos is taking an important position of status in the studying area of computer vision, pattern recognition and multimedia technology.
然后详细介绍了我们研发的一个视频监控系统中人脸识别系统的总体设计和实现细节，实验结果表明，该系统能够正常运行。
Then details of our R & D of a video monitoring system in the face recognition system, the overall design and implementation details, experimental results show that the system can function properly.
多摄像机环境中的人脸最优视角选择在多通道人机交互，视频会议，序列图像中的人脸识别等领域有着广泛的应用。
Best viewpoint selection in multiple cameras plays an important role in many applications such as human-machine interaction, videoconference, and face recognition in sequence images.
本系统包括视频捕获模块，人脸检测模块，特征提取模块及人脸识别模块。
This system includes video capture module, the face detect module, the feature extraction module and the face recognition module.
本文对智能视频监控的相关技术进行了探索和研究，重点对于视频监控中的目标识别和人脸匹配进行了研究和探讨。
In this paper, we explore and research intelligent video surveillance system with the relevant technology, focus on the object recognition and face matching in intelligent video surveillance system.
系统分为三部分，按数据流程的先后顺序，分别是视频采集模块、人脸检测和定位模块及人脸识别模块。
System consists of three parts, according to data flow in the order, respectively video capture module, face detection and localization module and face recognition module.
首先尝试运用数字图像处理与模式识别领域的知识对于视频图像序列进行图像预处理与人脸识别。
Knowledge about digital image processing and pattern recognition is applied to do image preprocessing and face recognition about video image sequences.
嘴唇是人脸特征的重要组成部分，在音视频识别、认证、嘴唇同步、人脸识别等方面都很重要。
Lip is one of the most important facial features, and plays key roles in a variety of fields such as audio-visual speech, authentication, lip synchronization, face recognition, etc.
基于视频监控的人脸识别技术是融合模式识别、视频图像处理、计算机视觉等多学科的具有挑战性的课题。
Face recognition based on video surveillance is a challenging task. It blends many subjects into a unity, such as pattern recognition, video image processing, computer vision, etc.
本文对于人脸检测、识别等问题进行了研究，针对视频中彩色图像提出了一种有关局部特征提取以及人脸识别的新方法。
The thesis has made a series of researching on face recognition-related problems, including automatic face detection, feature extraction, face recognition.
本文对于人脸检测、识别等问题进行了研究，针对视频中彩色图像提出了一种有关局部特征提取以及人脸识别的新方法。
The thesis has made a series of researching on face recognition-related problems, including automatic face detection, feature extraction, face recognition.
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