With the aging population and more and more people living alone, a fall detection system based on dual cameras is proposed to reduce the damage caused by falls. Aiming at the ghost problem of Vibe algorithm in the process of moving target detection, this study combines the frame difference method to judge ghost area, which speeds up ghost elimination and avoids its interference. The minimum outer rectangle of the human body is used to mark the detected human body, and the height, aspect ratio, centroid, and Hu moment characteristics of the outer rectangle are obtained. The fall detection algorithm based on threshold analysis and Support Vector Machine (SVM) is used to judge whether or not the human body falls. In order to improve the detection rate of fall behavior, dual cameras are proposed for joint judgment. The experimental results show that the system can effectively distinguish fall from other daily behaviors, and the algorithm has high accuracy and real-time performance.