The demand for interface technologies such as hand gesture detection is growing as virtual reality technology advances. In our study, we employed the state of art hand-tracking technology to construct an accurate and robust human-computer interaction(HCI) system. Our proposed method is cross-platform, lightweight, and effectively utilizes the resources from both CPU and GPU to achieve low latency performance. The MediaPipe framework, which yields a mean precision of 95.7 percent in palm identification, is used in this research to construct a realtime human-computer interaction interface that works properly regardless of difficult conditions such as different skin color, shape of hand, lighting condition, background, etc. Additionally, the speed of the proposed system is close to 40 fps acquired in a computer with weak hardware, which is sufficient for real-time HCI applications.