IntelliMotion: Real-Time Hand Gesture and Pose Tracking Using OpenCV and MediaPipe

Computer vision applications have been revolutionized by profound learning, which makes it conceivable to track human movement absolutely. An interesting hand signal and posture following framework that employs cutting-edge models to empower characteristic human-computer interaction is displayed in this paper. The framework precisely peruses hand signals and full-body postures, utilizing posture estimation and hand motion approaches for an assortment of applications, such as virtual reality, gaming, and wellness. The proposed strategy guarantees versatility in the assortment of lighting conditions and situations by combining real-time handling with profound learning-based feature extraction. The system's magnificent accuracy and responsiveness are outlined by the test that comes approximately, illustrating its potential for real-world utilization. The disclosures offer assistance inside the progression of movement area advancement by bridging the gap between human movements and computers. The system achieved an accuracy of approximately 90-95% for both hand and pose gesture recognition and maintained a real-time frame rate of 20–30 FPS on standard hardware.