Enabling Visual Scene Recovery from Wi-Fi CSI for Occlusion-Free Surveillance

Abstract

We introduce CSI-Inpainter, a novel approach for obstacle removal using Wi-Fi channel state information (CSI). This method harnesses CSI data to reconstruct obscured visual elements, regardless of lighting conditions. Extensive empirical evaluation in both office and industrial settings demonstrates the effectiveness of CSI-Inpainter’s exceptional ability to identify and reconstruct occluded segments, outperforming traditional baselines and our RSSI-based work, RF-Inpainter in terms of visual quality. Our findings emphasize the superiority of CSI data over RSSI for providing richer visual information and underscore the critical role of optimal sensor placement and data fusion from multiple CSI sensors in enhancing the performance. CSI-Inpainter represents a significant advancement in obstacle removal for various applications like surveillance, offering new insights into the integration of wireless sensing and visual scene recovery, expanding the potential applications of Computer Vision in real-world environments.