Robust face detection and recognition for computer-based security surveillance

用于基于计算机的安全监控的强大人脸检测和识别

• 批准号: LP0455257
• 负责人: A/Prof Andrew Paplinski
• 金额: $ 5.82万
• 依托单位: Monash University
• 依托单位国家: 澳大利亚
• 项目类别: Linkage Projects
• 财政年份: 2005
• 资助国家: 澳大利亚
• 起止时间: 2005-01-01 至 2008-01-31
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/LP0455257
• 关键词: Robust; face; detection; recognition; computer

The research aims at improving the existing and creating new automated face detection and recognition methods by making them invariant, firstly to head pose, orientation, scale and rotation, and then to occlusion, lighting conditions and facial expressions. A robust face detector will be developed first and then a new face recognition algorithm that continues to learn identity-specific discriminants on-line by collecting incremental face exemplars. The result of the research will be an algorithm that can improve its performance on-line adapting in a stable learning process each identity model to the correct facial examples. The research has significant practical implication in visual surveillance increasing the robustness of identification of person identity, state and intent.

该研究旨在改进现有的和创建新的自动人脸检测和识别方法，通过使它们不变性，首先是头部姿势，方向，尺度和旋转，然后是遮挡，光照条件和面部表情。 一个强大的人脸检测器将首先开发，然后一个新的人脸识别算法，继续学习身份特定的判别线收集增量人脸样本。研究的结果将是一个算法，可以提高其性能在线适应在一个稳定的学习过程中，每个身份模型正确的面部样本。 该研究对于提高视觉监控系统中身份、状态和意图识别的鲁棒性具有重要的实际意义。