For the tracking problem of moving pedestrians in indoor environment, this paper proposes a moving target tracking method based on the fusion of monocular vision and depth vision sensing information. Firstly, we use monocular vision image information to achieve target detection and complete semantic segmentation of the target. Then, we jointly calibrate monocular vision with depth vision to obtain the depth information of the recognition target by the depth camera. Finally, a moving target tracking method based on multi-camera information fusion is designed to address the problems of large error in monocular vision perspective-3-point (P3P) solution when the target is far away and slow frame rate of depth camera recognition, and the distance information obtained from monocular vision and depth information extracted from depth vision are asynchronously fused to achieve accurate estimation of the target motion state. The results show that the algorithm achieves the effect of real-time detection and tracking of pedestrian target positions within the field of view, with efficient target recognition and tracking capabilities.