High-profile speech videos are prime targets for falsification, owing to their accessibility and influence. This work proposes VeriLight, a low-overhead and unobtrusive system for protecting speech videos from visual manipulations of speaker identity and lip and facial motion. Unlike the predominant purely digital falsification detection methods, VeriLight creates dynamic physical signatures at the event site and embeds them into all video recordings via imperceptible modulated light. These physical signatures encode semantically-meaningful features unique to the speech event, including the speaker's identity and facial motion, and are cryptographically-secured to prevent spoofing. The signatures can be extracted from any video downstream and validated against the portrayed speech content to check its integrity. Key elements of VeriLight include (1) a framework for generating extremely compact (i.e., 150-bit), pose-invariant speech video features, based on locality-sensitive hashing; and (2) an optical modulation scheme that embeds $>$200 bps into video while remaining imperceptible both in video and live. Experiments on extensive video datasets show VeriLight achieves AUCs $\geq$ 0.99 and a true positive rate of 100% in detecting falsified videos. Further, VeriLight is highly robust across recording conditions, video post-processing techniques, and white-box adversarial attacks on its feature extraction methods. A demonstration of VeriLight is available at https://mobilex.cs.columbia.edu/verilight.

We present Phaser, a flexible system that directs narrow-beam laser light to moving robots for concurrent wireless power delivery and communication. We design a semiautomatic calibration procedure to enable fusion of stereo-vision-based 3D robot tracking with high-power beam steering, and a low-power optical communication scheme that reuses the laser light as a data channel. We fabricate a Phaser prototype using off-the-shelf hardware and evaluate its performance with battery-free autonomous robots. Phaser delivers optical power densities of over 110 mW/cm2and error-free data to mobile robots at multi-meter ranges, with on-board decoding drawing 0.3 mA (97% less current than Bluetooth Low Energy). We demonstrate Phaser fully powering gram-scale battery-free robots to nearly 2x higher speeds than prior work while simultaneously controlling them to navigate around obstacles and along paths. Code, an open-source design guide, and a demonstration video of Phaser is available at: mobilex.cs.columbia.edu/phaser

We present a high-speed underwater optical backscatter communication technique based on acousto-optic light steering. Our approach enables underwater assets to transmit data at rates potentially reaching hundreds of Mbps, vastly outperforming current state-of-the-art optical and underwater backscatter systems, which typically operate at only a few kbps. In our system, a base station illuminates the backscatter device with a pulsed laser and captures the retroreflected signal using an ultrafast photodetector. The backscatter device comprises a retroreflector and a 2 MHz ultrasound transducer. The transducer generates pressure waves that dynamically modulate the refractive index of the surrounding medium, steering the light either toward the photodetector (encoding bit 1) or away from it (encoding bit 0). Using a 3-bit redundancy scheme, our prototype achieves a communication rate of approximately 0.66 Mbps with an energy consumption of ≤ 1 μJ/bit, representing a 60× improvement over prior techniques. We validate its performance through extensive laboratory experiments in which remote underwater assets wirelessly transmit multimedia data to the base station under various environmental conditions.

Conventional wisdom holds that laser-based systems cannot handle mobility due to the strong directionality of laser light. We challenge this belief by presenting Lasertag, a generic system framework that tightly integrates laser steering with optical tracking to maintain laser connectivity with high-velocity targets. Lasertag creates a constantly connected, laser-based tether between the Lasertag core unit and a remote target, irrespective of the target's movement. Key elements of Lasertag include (1) a novel optical design that superimposes the optical paths of a steerable laser beam and an image sensor, (2) a lightweight optical tracking mechanism for passive retroreflective markers, (3) an automated mapping method to translate scene points to laser steering commands, and (4) a predictive steering algorithm that overcomes limited image sensor frame rates and laser steering delays to quadruple the steering rate up to 151 Hz. We demonstrate Lasertag's tethering capabilty with various mobile targets, such as a VR headset worn during active game play, a remotely-controlled moving robot, and more. Lasertag paves the way for laser applications in highly mobile settings.

Locating underwater robots is fundamental for enabling important underwater applications. The current mainstream method requires a physical infrastructure with relays on the water surface, which is largely ad-hoc, introduces a significant logistical overhead, and entails limited scalability. Our work, Sunflower, presents the first demonstration of wireless, 3D localization across the air-water interface - eliminating the need for additional infrastructure on the water surface. Specifically, we propose a laser-based sensing system to enable aerial drones to directly locate underwater robots. The Sunflower system consists of a queen and a worker component on a drone and each tracked underwater robot, respectively. To achieve robust sensing, key system elements include (1) a pinhole-based sensing mechanism to address the sensing skew at air-water boundary and determine the incident angle on the worker, (2) a novel optical-fiber sensing ring to sense weak retroreflected light, (3) a laser-optimized backscatter communication design that exploits laser polarization to maximize retroreflected energy, and (4) the necessary models and algorithms for underwater sensing. Real-world experiments demonstrate that our Sunflower system achieves average localization error of 9.7 cm with ranges up to 3.8 m and is robust against ambient light interference and wave conditions.

Research conducted in the field of localization with passive light, or using the intrinsic properties of light to determine a person's location, has seen increased growth in recent years. Specifically, fluorescent lights have been shown to exhibit distinct frequencies which can be recorded, along with their positions, for future lookup and positioning. Developments have been made in utilizing this phenomenon with a smartphone's high-resolution back-facing camera, however the constant flipping between the camera and the screen results in a poor user experience. In this paper, we propose an algorithm for extracting and analyzing both loop-shaped and tubular fluorescent lights. Similarly, we contribute an improved method for detecting frequency characteristics of unmodified fluorescent lights using a smartphone's front facing camera, therefore eliminating the need to constantly flip the phone.

With the extensive use of smartphones, technology improving secure communication between smartphones is a growing field of research. As a form of Visible Light Communication, a color video barcode system creates a smartphone-tosmartphone communication channel. This color video barcode system, effectively an evolved form of QR codes, provides a secure alternative to WiFi, Bluetooth, and Near Field Communication. Recent improvements in smartphone screen resolution and camera capabilities allow for data transmission with larger amounts of information. In this paper, we investigate if these hardware changes will allow for improvements in data transmission over a screen-to-camera color barcode link. Our system, TEtra- TRansmISsion (TETRIS) achieves a communication throughput of 311.22 Kbps with 90% accuracy. We discuss how this could be improved with further work.