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Neural Network Based Complex Visual Information Processing: Face Detection and Recognition

机译:基于神经网络的复杂视觉信息处理:脸部检测和识别

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This paper focuses on the issue of detecting and recognizing faces. The work is divided into three main categories. The first part is about detection of faces in constrained conditions. The second part focuses on creation of a different recognition approach. The third one is about the test with robotic devices. However mobile devices (such as robots, small CCD cameras or cheaper cell phones) have many limitations i.e. images quality or very limited computing performance. With respect to limitations the system manages two substantial parts. The first one is responsible for detecting a face in an image. The second one is responsible for calculating the information featured in a face image and recognition of that information. The system is able to process faces in realtime with minimal computation performance and to use minimal space for storing its data. The proposed system was tested on a face database. We have used a FDDB benchmark for an exact comparison.
机译:本文侧重于检测和识别面孔的问题。这项工作分为三个主要类别。第一部分是关于在受约束条件下的面部检测面。第二部分侧重于创建不同的识别方法。第三个是关于机器人设备的测试。然而,移动设备(例如机器人,小CCD摄像机或更便宜的手机)具有许多限制I.E。图像质量或非常有限的计算性能。关于限制,系统管理两个大部分部分。第一个负责检测图像中的面部。第二个负责计算面部图像中的信息并识别该信息。该系统能够使用最小的计算性能进行实时处理面部,并使用最小空间来存储其数据。在面部数据库中测试了所提出的系统。我们使用FDDB基准测试进行精确比较。

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