Ankur Aditya

Volumetric videoconferencing enables immersive six Degrees of Freedom interactions by jointly transmitting visual appearance and 3D geometry. However, delivering volumetric video over today’s networks remains challenging due to high bandwidth demands, strict real-time latency constraints, and frequent packet loss. We present ReVo, a loss-resilient volumetric videoconferencing system that jointly recovers RGB and depth content under packet loss while meeting real-time constraints. It decouples volumetric video into RGB and depth streams, selectively protects critical content using network-layer FEC, and reconstructs corrupted non-critical frames using a post-decode neural recovery module. Our evaluations using real-world loss traces show that ReVo improves median SSIM by up to 32% for RGB content and 13% for depth content, and reduces video freezes by up to 95.7% compared to existing techniques.

Recent trends in flexible antennas and printed circuit boards present an opportunity to leverage deformable substrates such as textiles to deploy large UHF, VHF and ISM band antenna arrays in smart homes. Low-frequency large antenna arrays are rarely deployed in indoor settings due to their large size which makes them bulky and difficult to deploy. By embedding these arrays on existing surfaces such as curtains, we can improve through-wall sensing, beamforming for IoT devices equipped with low-power radios and indoor localization of Bluetooth tags.However, antenna arrays on curtains present new challenges since deformation shifts their phase centers and changes the 3D positions of antennas. We present CurtainNet, a flexible UHFband antenna array on a large surface curtain that leverages a combination of optical and RF tracking to compensate for these changes while dealing with occlusions and phase changes. Results show that CurtainNet outperforms alternative methods by more than 155% in beamforming performance and increases indoor range by 20m.