SBIR Phase I: Novel photographic steganography to reduce digital piracy on live streaming platforms

SBIR 第一阶段：新颖的摄影隐写术，以减少直播平台上的数字盗版

• 批准号: 2014776
• 负责人: Eric Wengrowski
• 金额: $ 22.5万
• 依托单位: STEG AI CORPORATION
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2014776&HistoricalAwards=false
• 关键词: SBIR; Phase; Novel; photographic; steganography

The broader impact of this Small Business Innovation Research (SBIR) Phase I project will be to detect screen-to-camera video piracy, through first-in-kind development of a robust video piracy detection method that uniquely applies camera-display messaging to copyright protection, while maintaining network quality standards. Existing watermarking solutions cannot reliably handle video-in-video piracy, where users upload pirated media captured using a smartphone camera; either they fail to detect video piracy or exhibit injurious hypersensitivity. The proposed solution balances these two concerns by embedding unique and unextractable watermarks into video content, thereby improving the ability for platforms to accurately match uploaded content with messages in the copyright-protected database. The resulting technology will allow for the detection of copyright information in camera-captured images and video, so that distributors can automatically filter against the illegal sharing of copyright-protected material, dramatically reducing liability—and costly copyright infringement fines—for social media companies. This Small Business Innovation Research (SBIR) Phase I project seeks to develop an innovative camera-display message system that uses photographic steganography to embed covert messages in displayed video, addressing the need to detect screen-to-camera video piracy. Although photographic steganography has been applied to still images, video message embedding is complicated by the presence of perceptible artifacts that degrade visual quality. This project proposes to use novel spatio-temporal embedding that adapts to video content to reduce visual artifacts and support message recovery. This method circumvents the artifact-based constraints of traditional grid systems and will support the standard viewing quality. The following Phase I objectives will establish technical and commercial feasibility: 1) develop a video compression model that can handle multiple compression variations; 2) develop an optimal adaptive spatio-temporal embedding approach that reduces observed visual artifacts while maintaining a high accuracy rate; 3) design and implement a paired comparison protocol perceptual metric to evaluate video quality after message embedding; 4) develop a real-time robust screen detection and segmentation algorithm.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

这一小型企业创新研究（SBIR）第一阶段项目的更广泛影响将是通过首次开发一种强大的视频盗版检测方法来检测屏幕到摄像头的视频盗版，该方法独特地将摄像头显示消息应用于版权保护，同时保持网络质量标准。 现有的水印解决方案不能可靠地处理视频中视频盗版，其中用户上传使用智能手机摄像头捕获的盗版媒体;它们要么无法检测视频盗版，要么表现出有害的超敏反应。所提出的解决方案通过将唯一且不可提取的水印嵌入到视频内容中来平衡这两个问题，从而提高平台将上传内容与受版权保护的数据库中的消息准确匹配的能力。由此产生的技术将允许检测摄像头捕获的图像和视频中的版权信息，这样分销商就可以自动过滤非法共享受版权保护的材料，大大减少社会媒体公司的责任和昂贵的版权侵权罚款。这个小型企业创新研究（SBIR）第一阶段项目旨在开发一种创新的摄像头显示消息系统，该系统使用摄影隐写术将隐藏消息嵌入显示视频中，以满足检测屏幕到摄像头视频盗版的需求。 虽然摄影隐写术已被应用于静态图像，视频消息嵌入是复杂的存在可感知的文物，降低视觉质量。 该项目提出使用适应视频内容的新颖时空嵌入来减少视觉伪影并支持消息恢复。该方法避免了传统网格系统中基于伪影的约束，并将支持标准的观看质量。以下第一阶段目标将建立技术和商业可行性：1）开发一个视频压缩模型，可以处理多种压缩变化; 2）开发一个最佳的自适应时空嵌入方法，减少观察到的视觉伪影，同时保持高准确率; 3）设计和实现一个配对比较协议感知度量，以评估消息嵌入后的视频质量; 4）开发一个实时的强大的屏幕检测和分割算法。这个奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。