WiFi DensePose: WiFi-based dense human pose estimation system through walls (github.com)

WiFi DensePose has introduced a revolutionary system for dense human pose estimation using WiFi signals, eliminating the need for cameras. By harnessing Channel State Information (CSI) data, this innovative technology offers real-time pose detection with less than 50ms latency and supports tracking of up to 10 individuals simultaneously. Its privacy-first approach ensures that personal data remains secure, making it particularly relevant for applications in healthcare, fitness, smart homes, and security. The system's architecture includes components such as a CSI Data Collector, Signal Processor, and Neural Network Model, enabling robust pose keypoint extraction and multi-object tracking. With an enterprise-ready API featuring authentication and monitoring, WiFi DensePose is hardware agnostic, compatible with standard WiFi routers, and provides comprehensive analytics like fall detection and activity recognition. Available on PyPI and with a thorough command-line interface for system management, this tool is set to enhance various fields by integrating seamless pose estimation capabilities without compromising user privacy.