EAGER: Image and Video Forensics: Detecting Image Manipulation by Content Analysis

EAGER：图像和视频取证：通过内容分析检测图像操纵

• 批准号: 1353155
• 负责人: James O'Brien
• 金额: $ 19.27万
• 依托单位: University of California-Berkeley
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-10-01 至 2015-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1353155&HistoricalAwards=false
• 关键词: EAGER; Image; Video; Forensics; Detecting

The advent of sophisticated photo editing software has made it increasingly easier to manipulate digital images. Often visual inspection cannot definitively distinguish the resulting forgeries from authentic photographs. In response, forensic techniques have emerged to detect geometric or statistical inconsistencies that result from specific forms of photo manipulation. The PI aspires to develop new forensic methods based on geometric content analysis, which focus on finding inconsistencies in the geometric relationships among objects depicted in a photograph. The geometric relationships in a 2D image correspond to the projection of the relations that exist in the 3D scene; if a scene is known to contain a given relationship but the projected relation does not hold in the photograph, then one may conclude that the photograph is not a true projective image of the scene. With this in mind, the PI's goal in this exploratory project is to build a set of testable constraints that must be satisfied in real images, so that an unsatisfied constraint constitutes definitive, objective evidence of image manipulation. Fundamental challenges of this work include: developing tools for analysis from incomplete lighting information, building testable models of skin reflectance, accounting for structured uncertainty in feature comparison, and establishing method guidelines for forensic image analysis.Broader Impacts: This project will create tools for objectively detecting image manipulation, which will help reporters, law enforcement, scientists, and others differentiate between legitimate photographs and forged images. The products of this research will be communicated via academic publications and online source code. Collaborations with industrial partners will allow the research to have practical impact as well.

复杂的照片编辑软件的出现使处理数字图像变得越来越容易。通常，肉眼检查不能明确地区分由此产生的伪造照片和真实照片。作为回应，法医技术应运而生，以检测特定形式的照片处理导致的几何或统计不一致。PI渴望开发基于几何内容分析的新法医方法，专注于找出照片中描绘的对象之间几何关系的不一致之处。2D图像中的几何关系对应于3D场景中存在的关系的投影；如果已知场景包含给定关系，但投影关系在照片中不成立，则可以得出结论，该照片不是场景的真实投影图像。考虑到这一点，PI在这个探索性项目中的目标是建立一组必须在真实图像中满足的可测试约束，以便未满足的约束构成图像操纵的明确、客观的证据。这项工作的基本挑战包括：开发从不完整的照明信息中分析的工具，建立可测试的皮肤反射率模型，考虑特征比较中的结构性不确定性，以及建立法医图像分析的方法指南。广泛的影响：该项目将创建客观检测图像篡改的工具，这将帮助记者、执法部门、科学家和其他人区分合法照片和伪造图像。这项研究的成果将通过学术出版物和在线源代码进行交流。与行业合作伙伴的合作也将使这项研究产生实际影响。