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

SBIR 第二阶段：新颖的摄影隐写术，以减少直播平台上的数字盗版

• 批准号: 2208746
• 负责人: Eric Wengrowski
• 金额: $ 100万
• 依托单位: STEG AI CORPORATION
• 依托单位国家: 美国
• 项目类别: Cooperative Agreement
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-12-01 至 2024-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2208746&HistoricalAwards=false
• 关键词: SBIR; Phase; II; Novel; photographic

The broader impact of this Small Business Innovation Research (SBIR) Phase II project will be to reduce video and image copyright-related liability for social media companies and retain profits for digital media licensing companies and other content owners/distributors who are holding or enforcing content rights. Beyond content protection, the technology being developed can also address the emerging need for digital content authentication that can assure users the digital images or videos they are viewing are legitimate and not altered through the use of “deep-fake” or other similar technologies. Global piracy of digital video has been estimated to cost media providers, content creators, and legal distributors $67-$79 billion in lost revenue. While companies pay billions of dollars per year for sports broadcast rights, illegal sports streaming sites can generate enormous ad revenues at virtually no cost. With the advent of the internet and the abundance of high-quality recording equipment on small, portable devices, it has become easier for video pirates to capture and share copyrighted material. Using photographic steganography to mark copyrighted content with undetectable messages will provide stakeholders with built-in anti-piracy protections. This technology, in turn, will help ensure legal content distribution, content protection for producers, and content assurance for consumers. This Small Business Innovation Research (SBIR) Phase II project seeks to develop a competitive solution to copyright protection through imperceptible watermarking of digital images and digital videos using photographic steganography. This project is distinct from prior work in that it: (1) models the human vision system so that pixel modulations are machine-readable but imperceptible to humans; (2) robustly handles video compression algorithms like H.264, HEVC, MPEG, and VP9; (3) employs single-frame, synchronization-free methodology compatible with both still images and videos; (4) enables free-space light communication (light field messaging) using smartphone cameras; (5) works with ordinary camera and display hardware with no special spectrum or speed requirements; and (6) employs state-of-the-art deep learning algorithms trained with hundreds of thousands of images. The proposed product will be able to reliably detect screen-to-camera piracy while maintaining broadcast video quality standards. During this project, the technology will be strengthened in four key technical areas of development: (i) robustness to critical image/video mutations; (ii) real-time encoding; (iii) computationally efficient decoding; and (iv) industry-standard certification for visual quality.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.

小型企业创新研究(SBIR)第二阶段项目的更广泛影响将是减少社交媒体公司与视频和图像版权相关的责任，并为持有或执行内容权利的数字媒体授权公司和其他内容所有者/发行商保留利润。除了内容保护，正在开发的技术还可以满足对数字内容认证的新需求，这种需求可以向用户保证，他们正在观看的数字图像或视频是合法的，不会通过使用“深度假冒”或其他类似技术进行更改。据估计，全球数字视频盗版给媒体提供商、内容创作者和合法发行商造成了670亿至790亿美元的收入损失。虽然公司每年为体育转播权支付数十亿美元，但非法体育流媒体网站可以几乎零成本地产生巨额广告收入。随着互联网的出现和小型便携设备上大量的高质量记录设备，视频盗版者捕获和分享受版权保护的材料变得更加容易。使用照片隐写技术在受版权保护的内容上标记不可检测的信息，将为利益相关者提供内置的反盗版保护。反过来，这项技术将有助于确保合法的内容分发，为生产者提供内容保护，并为消费者提供内容保障。这一小型企业创新研究(SBIR)第二阶段项目寻求开发一种具有竞争力的解决方案，通过使用摄影隐写技术对数字图像和数字视频进行不可感知的水印来实现版权保护。该项目与以前的工作不同之处在于：(1)对人类视觉系统进行建模，使得像素调制是机器可读的，但人类无法察觉；(2)稳健地处理H.264、HEVC、MPEG和VP9等视频压缩算法；(3)采用与静止图像和视频兼容的单帧、无同步方法；(4)使用智能手机相机实现自由空间光通信(光场消息传递)；(5)与普通相机和显示硬件一起工作，没有特殊的频谱或速度要求；以及(6)使用最先进的深度学习算法对数十万张图像进行训练。拟议的产品将能够可靠地检测到屏幕到摄像机的盗版，同时保持广播视频质量标准。在这个项目中，这项技术将在四个关键技术领域得到加强：(I)对关键图像/视频突变的稳健性；(Ii)实时编码；(Iii)计算效率解码；以及(Iv)视觉质量行业标准认证。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。