Improving human perception of low resolution face images

改善人类对低分辨率人脸图像的感知

• 批准号: DP150100684
• 负责人: Prof Elinor McKone
• 金额: $ 34.95万
• 依托单位: The Australian National University
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2015
• 资助国家: 澳大利亚
• 起止时间: 2015-04-30 至 2022-12-31
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP150100684
• 关键词: Improving; human; perception; low; resolution

Low-resolution face images occur in several settings that require a human observer to identify the face or its expression. For example, a crime eyewitness may have seen the perpetrator's face blurred by distance. This project aims to improve low-resolution face perception. Previous approaches have attempted only to improve general image visibility. Here, the novel theoretical idea is to alter the face's structure, tapping knowledge about higher-level face coding. Manipulations are caricaturing and whole-then-part alternation, as derived from face-space and holistic processing theories, respectively. Effects of viewpoint and own-versus-other race faces are expected to test practical generalisability of the new methods, and thus refine theory.

低分辨率人脸图像出现在需要人类观察者识别人脸或其表情的几种设置中。例如，犯罪目击者可能看到犯罪者的脸因距离而模糊。该项目旨在改善低分辨率人脸感知。以前的方法仅尝试提高一般图像的可见性。在这里，新颖的理论思想是改变人脸的结构，利用更高层次的人脸编码知识。操纵是漫画和整体然后部分交替，分别来自面孔空间和整体加工理论。观点和自己与其他种族面孔的影响预计将测试新方法的实际普适性，从而完善理论。