Abstract: Intelligent monitoring ball machine is widely used in indoor intelligent monitoring. Aiming at the problem of long-term detection, recognition and tracking of intrusive targets, this paper designs and implements a closed-loop structure combining target detection, target recognition and target tracking algorithm, and uses control algorithm to control the ball machine platform to automatically follow the intrusive targets. Vibe algorithm is used for moving target detection and neural network is applied for target recognition, where single shot multi box detector (SSD) network is used to detect face and yolov3 (You only look once) network is used to recognize human body. After recognizing the tracking target, discriminative correlation filter with channel and spatial reliability (csr-dcf) target tracking algorithm is used to track the target. In the tracking mode, the fuzzy pid control algorithm is started to control the platform to follow the target rotation, and after locking the target, the tracking mode is used to track the target. The model is switched to target recognition mode again, forming a closed loop of detection, recognition, tracking and control. The test shows that this method improves the robustness of intrusion tracking function, and can be tracked for a long time in the case of fast movement of the intrusive target, occlusion and temporary disappearance.