A multi-faces tracking and recognition framework for surveillance system

Huafeng Wang, Yunhong Wang, Zhaoxiang Zhang, Fan Wang, Jin Huang
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引用次数: 1

Abstract

A novel framework for unsupervised multi-faces tracking and recognition is built on Detection-Tracking-Recognition (DTR) approach. This framework proposed a hybrid face detector for real-time face tracking which is robust to occlusions and posture changes. Faces acquired during unsupervised detection stage will be further processed by SIFT operator in order to cluster face sequence into certain groups. After that, the relevant faces are put together which is of much importance for face recognition in videos. The framework is validated on several videos collected in unconstrained condition (20min each.).The framework can track the face and automatically group a serial faces for a single human-being object in an unlabeled video robustly.
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一种用于监控系统的人脸跟踪与识别框架
基于检测-跟踪-识别(Detection-Tracking-Recognition, DTR)方法,提出了一种新的无监督人脸跟踪与识别框架。该框架提出了一种对遮挡和姿态变化具有鲁棒性的实时人脸跟踪混合检测器。在无监督检测阶段获得的人脸将被SIFT算子进一步处理,将人脸序列聚类成特定的组。然后将相关的人脸组合在一起,这对视频中的人脸识别非常重要。该框架在无约束条件下收集的多个视频(每个20分钟)上进行验证。该框架可以对人脸进行跟踪,并对未标记视频中单个人类对象的连续人脸进行鲁棒分组。
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