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操纵数字图像变得越来越容易。 通常，视觉检查不能明确地将产生的伪造与真实的照片区分开。 作为响应，已出现法医技术来检测特定形式的照片操作导致的几何或统计不一致。 PI渴望根据几何含量分析开发新的法医方法，该方法的重点是在照片中描绘的对象之间找到几何关系中的矛盾。 2D图像中的几何关系对应于3D场景中存在的关系的投影；如果已知一个场景包含给定的关系，但是预计的关系不存在，那么人们可能会得出结论，照片不是场景的真正投射图像。 考虑到这一点，PI在此探索性项目中的目标是建立一组可测试的约束，这些约束必须在真实的​​图像中满足，因此不满意的约束构成了对图像操纵的确定性，客观的证据。 这项工作的基本挑战包括：从不完整的照明信息中开发工具，建立可测试的皮肤反射率模型，考虑到功能比较中的结构不确定性以及建立法医图像分析的方法指南。BOADER的影响：该项目将创建客观地检测图像管理的工具，这些工具将帮助探测图像管理，这将帮助记者，法律执行学家，以及范围的图像，以及其他不同的图像。 这项研究的产品将通过学术出版物和在线源代码进行传达。 与工业合作伙伴的合作将使研究也可以实现影响。