Light Field Messaging (LFM) is a process of embedding, transmitting, and receiving hidden information in video that is displayed on a screen and captured by a handheld camera. The goal of the system is to minimize perceived visual artifacts of the message embedding, while simultaneously maximizing the accuracy of message recovery on the camera side. LFM requires photographic steganography for embedding messages that can be displayed on a screen and captured by a camera. Unlike digital
steganography, the embedding requirements are significantly more challenging due to the combined effect of the screens’ diverse radiometric emittance functions, the cameras’ variable sensitivity functions, and the camera-display relative geometry.
Scientists at Rutgers have devised and trained an AI network to jointly learn a deep embedding and recovery algorithm that requires no multi-frame synchronization. A key novel component is the camera display transfer function (CDTF) to model the camera-display pipeline. The result of this novel work is a high-performance real-time LFM system using consumer-grade displays and smartphone cameras.
· Invisible to humans.
· Robust to diverse camera and display hardware combinations.
· No temporal synchronization required.
· Accurate message transmission and recovery.
· Better bit-error-rate than existing deep-learning and fixed-filter steganography approaches.
1) Anti-piracy water-marking.
2) Imperceptible messaging for consumer engagement and increased purchases.